├── TableComparison.png ├── QWENsettingsNODRAFT.me ├── QWENsettingsDRAFT.me ├── Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885.csv ├── Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF.csv ├── README.md ├── promptLibv2DRAFT.py ├── 102.QWEN2.5-instruct_LlamaCPPSERVER-NODRAFT_API_promptTest.py ├── 101.QWEN2.5-instruct_LlamaCPPSERVER-DRAFT_API_promptTest.py ├── Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt └── Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt /TableComparison.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/fabiomatricardi/llamacpp-speculative/main/TableComparison.png -------------------------------------------------------------------------------- /QWENsettingsNODRAFT.me: -------------------------------------------------------------------------------- 1 | { 2 | "port" : 8001, 3 | "models": [ 4 | { 5 | "model": "models/Qwen2.5-7B-Instruct-Q4_0.gguf", 6 | "model_alias": "QWEN2.5", 7 | "n_ctx": 8196 8 | } 9 | ] 10 | } -------------------------------------------------------------------------------- /QWENsettingsDRAFT.me: -------------------------------------------------------------------------------- 1 | { 2 | "port" : 8001, 3 | "models": [ 4 | { 5 | "model": "models/Qwen2.5-7B-Instruct-Q4_0.gguf", 6 | "model_alias": "QWEN2.5", 7 | "n_ctx": 8196, 8 | "draft_model" : "models/Qwen2.5-0.5B-Instruct-Q8_0.gguf", 9 | "draft_model_num_pred_tokens" : 2 10 | } 11 | ] 12 | } -------------------------------------------------------------------------------- /Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885.csv: -------------------------------------------------------------------------------- 1 | #,TASK,GENSPEED,INFSPEED,TTFT,TIME 2 | 1,introduction,6.06,7.50,1.09,10.40 3 | 2,explain in one sentence,5.74,7.25,0.97,6.62 4 | 3,explain in three paragraphs,6.68,6.99,1.08,38.19 5 | 4,say 'I am ready',0.91,95.10,3.75,4.40 6 | 5,summarize,5.43,19.34,3.35,29.11 7 | 6,Summarize in two sentences,4.34,36.18,3.57,12.91 8 | 7,Write in a list the three main key points - format output,4.70,33.81,3.68,14.67 9 | 8,Table of Contents,4.53,31.53,3.70,15.67 10 | 9,RAG,4.55,29.55,3.72,17.60 11 | 10,Truthful RAG,0.71,108.37,3.77,4.25 12 | 11,write content from a reference,5.69,10.95,3.42,82.94 13 | 12,extract 5 topics,5.84,15.18,3.69,43.68 14 | 13,Creativity: 1000 words SF story,6.41,6.88,2.04,149.23 15 | 14,Reflection prompt,6.46,9.62,3.31,108.55 16 | -------------------------------------------------------------------------------- /Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF.csv: -------------------------------------------------------------------------------- 1 | ,,,,,,,,,, 2 | ,,WITH SPECULATIVE DECODING,,,,,NO DRAFT MODEL,,, 3 | #,TASK,GENSPEED,INFSPEED,TTFT,TIME,,GENSPEED,INFSPEED,TTFT,TIME 4 | 1,introduction,5.01,6.72,1.21,8.78,,6.06,7.5,1.09,10.4 5 | 2,explain in one sentence,4.4,5.56,1.15,8.64,,5.74,7.25,0.97,6.62 6 | 3,explain in three paragraphs,4.86,5.17,0.99,37.89,,6.68,6.99,1.08,38.19 7 | 4,say 'I am ready',0.9,94.3,3.8,4.43,,0.91,95.1,3.75,4.4 8 | 5,summarize,4.07,13.71,3.35,42.03,,5.43,19.34,3.35,29.11 9 | 6,Summarize in two sentences,3.25,27.14,3.64,17.2,,4.34,36.18,3.57,12.91 10 | 7,Write in a list the three main key points - format output,4.25,29.14,3.67,17.16,,4.7,33.81,3.68,14.67 11 | 8,Table of Contents,3.59,24.95,3.6,19.8,,4.53,31.53,3.7,15.67 12 | 9,RAG,3.66,23.76,3.84,21.89,,4.55,29.55,3.72,17.6 13 | 10,Truthful RAG,0.73,112.25,3.8,4.11,,0.71,108.37,3.77,4.25 14 | 11,write content from a reference,4.43,8.72,3.41,101.72,,5.69,10.95,3.42,82.94 15 | 12,extract 5 topics,4.54,12.84,3.72,49.15,,5.84,15.18,3.69,43.68 16 | 13,Creativity: 1000 words SF story,4.54,4.79,2.05,279.29,,6.41,6.88,2.04,149.23 17 | 14,Reflection prompt,5.06,7.21,3.19,159.71,,6.46,9.62,3.31,108.55 18 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # llamacpp-speculative decoding 2 | Comparison of using llama.cpp llama-cpp-python server with speculative decoding and without it 3 | 4 | > There is really no benefit? 5 | 6 | In my findings, without offloading any layer oì to GPU, there are no increase in speed. 7 | 8 | ## Comparison table 9 | 10 | 11 | 12 | 13 | ## STACK 14 | - llama-cpp-python[server] revision 0.3.2 that supports also Granite3, OLMO and MoE 15 | - openAI pytho library to access the endpoints 16 | - automatic prompt evaluation 17 | - server settings as per [documentation](https://llama-cpp-python.readthedocs.io/en/latest/server/) 18 | 19 | ## Dependencies 20 | - llama-cpp-python[server]==0.3.2 21 | - openai 22 | - tiktoken 23 | 24 | 25 | ## How to use 26 | ### with speculative decoding 27 | from one terminal window run 28 | ``` 29 | python -m llama_cpp.server --config_file .\QWENsettingsDRAFT.me 30 | ``` 31 | Using the following server settings 32 | ``` 33 | { 34 | "port" : 8001, 35 | "models": [ 36 | { 37 | "model": "models/Qwen2.5-7B-Instruct-Q4_0.gguf", 38 | "model_alias": "QWEN2.5", 39 | "n_ctx": 8196, 40 | "draft_model" : "models/Qwen2.5-0.5B-Instruct-Q8_0.gguf", 41 | "draft_model_num_pred_tokens" : 2 42 | } 43 | ] 44 | } 45 | ``` 46 | In another terminal window run 47 | ``` 48 | python .\101.QWEN2.5-instruct_LlamaCPPSERVER-DRAFT_API_promptTest.py 49 | ``` 50 | 51 | ### WITHOUT speculative decoding 52 | from one terminal window run 53 | ``` 54 | python -m llama_cpp.server --config_file .\QWENsettingsNODRAFT.me 55 | ``` 56 | Using the following server settings 57 | ``` 58 | { 59 | "port" : 8001, 60 | "models": [ 61 | { 62 | "model": "models/Qwen2.5-7B-Instruct-Q4_0.gguf", 63 | "model_alias": "QWEN2.5", 64 | "n_ctx": 8196 65 | } 66 | ] 67 | } 68 | ``` 69 | In another terminal window run 70 | ``` 71 | python .\102.QWEN2.5-instruct_LlamaCPPSERVER-NODRAFT_API_promptTest.py 72 | ``` 73 | 74 | 75 | -------------------------------------------------------------------------------- /promptLibv2DRAFT.py: -------------------------------------------------------------------------------- 1 | """ 2 | V2 changes 3 | added Time To First Token in the statistics ttft 4 | added some more prompts in the catalog 5 | - say 'I am ready' 6 | - modified for Llama3.2-1b Write in a list the three main key points - format output 7 | 8 | 20240929 FAMA 9 | """ 10 | 11 | import random 12 | import string 13 | import tiktoken 14 | 15 | def createCatalog(): 16 | """ 17 | Create a dictionary with 18 | 'task' : description of the NLP task in the prompt 19 | 'prompt' : the instruction prompt for the LLM 20 | """ 21 | context = """One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 22 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 23 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 24 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 25 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 26 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 27 | It could soon be the case that the so-called developing countries will be showing the West the way forward.""" 28 | catalog = [] 29 | prmpt_tasks = ["introduction", 30 | "explain in one sentence", 31 | "explain in three paragraphs", 32 | "say 'I am ready'", 33 | "summarize", 34 | "Summarize in two sentences", 35 | "Write in a list the three main key points - format output", 36 | "Table of Contents", 37 | "RAG", 38 | "Truthful RAG", 39 | "write content from a reference", 40 | "extract 5 topics", 41 | "Creativity: 1000 words SF story", 42 | "Reflection prompt" 43 | ] 44 | prmpt_coll = [ 45 | """Hi there I am Fabio, a Medium writer. who are you?""", 46 | """explain in 1 sentence what is science.\n""", 47 | """explain only in 3 paragraphs what is artificial intelligence.\n""", 48 | f"""read the following text and when you are done say "I am ready". 49 | 50 | [text] 51 | {context} 52 | [end of text] 53 | 54 | """, 55 | f"""summarize the following text: 56 | [text] 57 | {context} 58 | [end of text] 59 | 60 | """, 61 | f"""Write a summary of the following text. Use only 2 sentences. 62 | [text] 63 | {context} 64 | [end of text] 65 | 66 | """, 67 | f"""1. extract the 3 key points from the provided text 68 | 2. format the output as a python list. 69 | [text] 70 | {context} 71 | [end of text] 72 | Return only the python list. 73 | """, 74 | f"""write a "table of contents" of the provided text. Be simple and concise. 75 | [text] 76 | {context} 77 | [end of text] 78 | 79 | "table of content": 80 | """, 81 | f"""Reply to the question using the provided context. If the answer is not contained in the text say "unanswerable". 82 | [context] 83 | {context} 84 | [end of context] 85 | 86 | question: what China achieved with it's long-term planning? 87 | answer: 88 | """, 89 | f"""Reply to the question only using the provided context. If the answer is not contained in the provided context say "unanswerable". 90 | 91 | question: who is Anne Frank? 92 | 93 | [context] 94 | {context} 95 | [end of context] 96 | 97 | Remember: if you cannot answer based on the provided context, say "unanswerable" 98 | 99 | answer: 100 | """, 101 | 102 | f"""Using the following text as a reference, write a 5-paragraphs essay about "the benefits of China economic model". 103 | 104 | [text] 105 | {context} 106 | [end of text] 107 | Remember: use the information provided and write exactly 5 paragraphs. 108 | """, 109 | f"""List 5 most important topics from the following text: 110 | [text] 111 | {context} 112 | [end of text] 113 | """, 114 | """Science Fiction: The Last Transmission - Write a story that takes place entirely within a spaceship's cockpit as the sole surviving crew member attempts to send a final message back to Earth before the ship's power runs out. The story should explore themes of isolation, sacrifice, and the importance of human connection in the face of adversity. 800-1000 words. 115 | 116 | """, 117 | """You are an AI assistant designed to provide detailed, step-by-step responses. Your outputs should follow this structure: 118 | 1. Begin with a section. 119 | 2. Inside the thinking section: 120 | a. Briefly analyze the question and outline your approach. 121 | b. Present a clear plan of steps to solve the problem. 122 | c. Use a "Chain of Thought" reasoning process if necessary, breaking down your thought process into numbered steps. 123 | 3. Include a section for each idea where you: 124 | a. Review your reasoning. 125 | b. Check for potential errors or oversights. 126 | c. Confirm or adjust your conclusion if necessary. 127 | 4. Be sure to close all reflection sections. 128 | 5. Close the thinking section with . 129 | 6. Provide your final answer in an section. 130 | Always use these tags in your responses. Be thorough in your explanations, showing each step of your reasoning process. Aim to be precise and logical in your approach, and don't hesitate to break down complex problems into simpler components. Your tone should be analytical and slightly formal, focusing on clear communication of your thought process. 131 | Remember: Both and MUST be tags and must be closed at their conclusion 132 | Make sure all are on separate lines with no other text. Do not include other text on a line containing a tag. 133 | 134 | user question: explain why it is crucial for teachers to learn how to use generative AI for their job and for the future of education. Include relevant learning path for teachers and educators. 135 | 136 | """ 137 | ] 138 | for i in range(0,len(prmpt_tasks)): 139 | catalog.append({'task':prmpt_tasks[i], 140 | 'prompt': prmpt_coll[i]}) 141 | return catalog 142 | 143 | def countTokens(text): 144 | """ 145 | Use tiktoken to count the number of tokens 146 | text -> str input 147 | Return -> int number of tokens counted 148 | """ 149 | encoding = tiktoken.get_encoding("r50k_base") #context_count = len(encoding.encode(yourtext)) 150 | numoftokens = len(encoding.encode(text)) 151 | return numoftokens 152 | 153 | def writehistory(filename,text): 154 | """ 155 | save a string into a logfile with python file operations 156 | filename -> str pathfile/filename 157 | text -> str, the text to be written in the file 158 | """ 159 | with open(f'{filename}', 'a', encoding='utf-8') as f: 160 | f.write(text) 161 | f.write('\n') 162 | f.close() 163 | 164 | def genRANstring(n): 165 | """ 166 | n = int number of char to randomize 167 | """ 168 | N = n 169 | res = ''.join(random.choices(string.ascii_uppercase + 170 | string.digits, k=N)) 171 | return res 172 | 173 | def createStats(delta,question,output,rating,logfilename,task,ttft): 174 | """ 175 | Takes in all the generation main info and return KPIs 176 | delta -> datetime.now() delta 177 | question -> str the user input to the LLM 178 | output -> str the generation from the LLM 179 | rating -> str human eval feedback rating 180 | logfilename -> str filepath/filename 181 | task -> str description of the NLP task describing the prompt 182 | ttft -> datetime.now() delta time to first token 183 | """ 184 | totalseconds = delta.total_seconds() 185 | prompttokens = countTokens(question) 186 | assistanttokens = countTokens(output) 187 | totaltokens = prompttokens + assistanttokens 188 | speed = totaltokens/totalseconds 189 | genspeed = assistanttokens/totalseconds 190 | ttofseconds = ttft.total_seconds() 191 | stats = f'''--- 192 | Prompt Tokens: {prompttokens} 193 | Output Tokens: {assistanttokens} 194 | TOTAL Tokens: {totaltokens} 195 | >>>⏱️ Time to First Token: {ttofseconds:.2f} seconds 196 | >>>⏱️ Inference time: {delta} 197 | >>>🧮 Inference speed: {speed:.3f} t/s 198 | >>>🏍️ Generation speed: {genspeed:.3f} t/s 199 | >>>📝 Logfile: {logfilename} 200 | >>>💚 User rating: {rating} 201 | >>>✅ NLP TAKS: {task} 202 | ''' 203 | return stats,totalseconds,speed,genspeed,ttofseconds -------------------------------------------------------------------------------- /102.QWEN2.5-instruct_LlamaCPPSERVER-NODRAFT_API_promptTest.py: -------------------------------------------------------------------------------- 1 | # Chat with an intelligent assistant in your terminal 2 | # DRAFT MODEL: Qwen2.5-0.5B-Instruct-Q8_0.gguf 3 | # INFERENCE model: Qwen2.5-7B-Instruct-Q4_0.gguf 4 | ########################################################################## 5 | import sys 6 | from time import sleep 7 | import warnings 8 | warnings.filterwarnings(action='ignore') 9 | import datetime 10 | from promptLibv2DRAFT import countTokens, writehistory, createCatalog 11 | from promptLibv2DRAFT import genRANstring, createStats 12 | from openai import OpenAI 13 | ## PREPARING FINAL DATASET 14 | 15 | pd_id = [] 16 | pd_task = [] 17 | pd_speed = [] 18 | pd_infspeed = [] 19 | pd_ttft = [] 20 | pd_time = [] 21 | 22 | ####################INITIALIZE THE MODEL################################### 23 | STOPS=['<|im_end|>'] 24 | tasks = createCatalog() 25 | NCTX = 8196 26 | modelname = 'Qwen2.5-7B-Instruct-Q4_0.gguf' 27 | # create THE LOG FILE 28 | coded5 = genRANstring(5) 29 | logfile = f'Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_{coded5}_log.txt' 30 | csvfile = f'Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_{coded5}.csv' 31 | logfilename = logfile 32 | #Write in the history the first 2 sessions 33 | writehistory(logfilename,f'''{str(datetime.datetime.now())} 34 | --- 35 | Your own LocalGPT with 💻 {modelname} 36 | --- 37 | 🧠🫡: You are a helpful assistant. 38 | temperature: 0.15 39 | repeat penalty: 1.31 40 | max tokens: 1500 41 | ---''') 42 | writehistory(logfilename,f'💻: How can I assist you today in writing?') 43 | # LOAD THE MODEL 44 | print("\033[95;3;6m") 45 | print("1. Waiting 10 seconds for the API to load...") 46 | llm = OpenAI(base_url="http://localhost:8001/v1", api_key="not-needed", organization=modelname) 47 | print(f"2. Model {modelname} loaded with LlamaCPP...") 48 | print("\033[0m") #reset all 49 | history = [] 50 | print("\033[92;1m") 51 | print(f'📝Logfile: {logfilename}') 52 | ##################### ALIGNMENT FIRST GENERATION ############################################## 53 | question = 'Explain the plot of Cinderella in one sentence.' 54 | test = [ 55 | {"role": "user", "content": question} 56 | ] 57 | print('Question:', question) 58 | start = datetime.datetime.now() 59 | print("💻 > ", end="", flush=True) 60 | full_response = "" 61 | fisrtround = 0 62 | completion = llm.chat.completions.create( 63 | model="local-model", # this field is currently unused 64 | messages=test, 65 | temperature=0.25, 66 | frequency_penalty = 1.53, 67 | max_tokens = 1200, 68 | stream=True, 69 | stop=STOPS 70 | ) 71 | for chunk in completion: 72 | if chunk.choices[0].delta.content: 73 | if fisrtround==0: 74 | print(chunk.choices[0].delta.content, end="", flush=True) 75 | full_response += chunk.choices[0].delta.content 76 | ttftoken = datetime.datetime.now() - start 77 | fisrtround = 1 78 | else: 79 | print(chunk.choices[0].delta.content, end="", flush=True) 80 | full_response += chunk.choices[0].delta.content 81 | delta = datetime.datetime.now() - start 82 | output = full_response 83 | print('') 84 | print("\033[91;1m") 85 | rating = input('Rate from 0 (BAD) to 5 (VERY GOOD) the quality of generation> ') 86 | print("\033[92;1m") 87 | stats = createStats(delta,question,output,rating,logfilename,'Alignment Generation',ttftoken) 88 | print(stats) 89 | writehistory(logfilename,f'''👨‍💻 . {question} 90 | 💻 > {output} 91 | {stats} 92 | ''') 93 | 94 | ############################# AUTOMATIC PROMPTING EVALUATION 11 TURNS ################################# 95 | id =1 96 | for items in tasks: 97 | fisrtround = 0 98 | task = items["task"] 99 | prompt = items["prompt"] 100 | test = [] 101 | print(f'NLP TAKS>>> {task}') 102 | print("\033[91;1m") #red 103 | print(prompt) 104 | test.append({"role": "user", "content": prompt}) 105 | print("\033[92;1m") 106 | full_response = "" 107 | start = datetime.datetime.now() 108 | print("💻 > ", end="", flush=True) 109 | completion = llm.chat.completions.create( 110 | model="local-model", # this field is currently unused 111 | messages=test, 112 | temperature=0.25, 113 | frequency_penalty = 1.53, 114 | max_tokens = 1200, 115 | stream=True, 116 | stop=STOPS 117 | ) 118 | for chunk in completion: 119 | if chunk.choices[0].delta.content: 120 | if fisrtround==0: 121 | print(chunk.choices[0].delta.content, end="", flush=True) 122 | full_response += chunk.choices[0].delta.content 123 | ttftoken = datetime.datetime.now() - start 124 | fisrtround = 1 125 | else: 126 | print(chunk.choices[0].delta.content, end="", flush=True) 127 | full_response += chunk.choices[0].delta.content 128 | delta = datetime.datetime.now() - start 129 | print('') 130 | print("\033[91;1m") 131 | rating = 'All good here only speed test with speculative decoding'#input('Rate from 0 (BAD) to 5 (VERY GOOD) the quality of generation> ') 132 | print("\033[92;1m") 133 | stats,totalseconds,speed,genspeed,ttofseconds = createStats(delta,prompt,full_response,rating,logfilename,task,ttftoken) 134 | print(stats) 135 | writehistory(logfilename,f'''👨‍💻 > {prompt} 136 | 💻 > {full_response} 137 | {stats} 138 | ''') 139 | pd_id.append(id) 140 | pd_task.append(task) 141 | pd_speed.append(f'{genspeed:.2f}') 142 | pd_infspeed.append(f'{speed:.2f}') 143 | pd_ttft.append(f'{ttofseconds:.2f}') 144 | pd_time.append(f'{totalseconds:.2f}') 145 | id += 1 146 | # create dataframe and save to csv 147 | zipped = list(zip(pd_id,pd_task,pd_speed,pd_infspeed,pd_ttft,pd_time)) 148 | import pandas as pdd 149 | df = pdd.DataFrame(zipped, columns=['#', 'TASK', 'GENSPEED','INFSPEED','TTFT','TIME']) 150 | #saving the DataFrame as a CSV file 151 | df_csv_data = df.to_csv(csvfile, index = False, encoding='utf-8') 152 | print('\nCSV String:\n', df) 153 | from rich.console import Console 154 | console = Console() 155 | console.print('---') 156 | console.print(df) 157 | 158 | 159 | 160 | ##############MODEL CARD########################################## 161 | """ 162 | # Chat with an intelligent assistant in your terminal 163 | # MODEL: https://huggingface.co/bartowski/AMD-OLMo-1B-SFT-DPO-GGUF 164 | # Original model: https://huggingface.co/amd/AMD-OLMo-1B-SFT-DPO 165 | # AMD-OLMo-1B-SFT-DPO-Q6_K_L.gguf 166 | MODELCARD 167 | =========================================================== 168 | mp = 'models/AMD-OLMo-1B-SFT-DPO-Q6_K_L.gguf' 169 | from llama_cpp import Llama 170 | llm = Llama(model_path = mp) 171 | 172 | CHAT TEMPLATE = yes 173 | NCTX = 2048 174 | 175 | Prompt format 176 | ``` 177 | <|system|> 178 | {system_prompt} 179 | <|user|> 180 | {prompt} 181 | <|assistant|> 182 | ``` 183 | 184 | Available chat formats from metadata: chat_template.default 185 | Using gguf chat template: {% for message in messages %} 186 | {% if message['role'] == 'user' %} 187 | {{ '<|user|> 188 | ' + message['content'] }} 189 | {% elif message['role'] == 'system' %} 190 | {{ '<|system|> 191 | ' + message['content'] }} 192 | {% elif message['role'] == 'assistant' %} 193 | {{ '<|assistant|> 194 | ' + message['content'] }} 195 | {% endif %} 196 | {% if loop.last and add_generation_prompt %} 197 | {{ '<|assistant|>' }} 198 | {% endif %} 199 | {% endfor %} 200 | Using chat eos_token: |||IP_ADDRESS||| 201 | Using chat bos_token: |||IP_ADDRESS||| 202 | 203 | 204 | llama_model_loader: loaded meta data with 33 key-value pairs and 113 tensors from models/AMD-OLMo-1B-SFT-DPO-Q6_K_L.gguf (version GGUF V3 (latest)) 205 | llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. 206 | general.architecture str = olmo 207 | general.type str = model 208 | general.name str = AMD OLMo 1B SFT DPO 209 | general.finetune str = SFT-DPO 210 | general.basename str = AMD-OLMo 211 | general.size_label str = 1B 212 | general.license str = apache-2.0 213 | general.datasets arr[str,1] = ["allenai/dolma"] 214 | olmo.block_count u32 = 16 215 | olmo.context_length u32 = 2048 216 | olmo.embedding_length u32 = 2048 217 | olmo.feed_forward_length u32 = 8192 218 | olmo.attention.head_count u32 = 16 219 | olmo.attention.head_count_kv u32 = 16 220 | olmo.rope.freq_base f32 = 10000.000000 221 | general.file_type u32 = 18 222 | olmo.attention.layer_norm_epsilon f32 = 0.000010 223 | tokenizer.ggml.model str = gpt2 224 | tokenizer.ggml.pre str = olmo 225 | tokenizer.ggml.tokens arr[str,50304] = ["<|endoftext|>", "<|padding|>", "!",... 226 | tokenizer.ggml.token_type arr[i32,50304] = [3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... 227 | tokenizer.ggml.merges arr[str,50009] = ["Ġ Ġ", "Ġ t", "Ġ a", "h e", "i n... 228 | tokenizer.ggml.bos_token_id u32 = 50279 229 | tokenizer.ggml.eos_token_id u32 = 50279 230 | tokenizer.ggml.padding_token_id u32 = 1 231 | tokenizer.ggml.add_bos_token bool = false 232 | tokenizer.ggml.add_eos_token bool = false 233 | tokenizer.chat_template str = {% for message in messages %}\n{% if m... 234 | general.quantization_version u32 = 2 235 | quantize.imatrix.file str = /models_out/AMD-OLMo-1B-SFT-DPO-GGUF/... 236 | quantize.imatrix.dataset str = /training_dir/calibration_datav3.txt 237 | quantize.imatrix.entries_count i32 = 112 238 | quantize.imatrix.chunks_count i32 = 132 239 | llama_model_loader: - type q8_0: 1 tensors 240 | llama_model_loader: - type q6_K: 112 tensors 241 | llm_load_vocab: special tokens cache size = 28 242 | llm_load_vocab: token to piece cache size = 0.2985 MB 243 | llm_load_print_meta: format = GGUF V3 (latest) 244 | llm_load_print_meta: arch = olmo 245 | llm_load_print_meta: vocab type = BPE 246 | llm_load_print_meta: n_vocab = 50304 247 | llm_load_print_meta: n_merges = 50009 248 | llm_load_print_meta: vocab_only = 0 249 | llm_load_print_meta: n_ctx_train = 2048 250 | llm_load_print_meta: n_embd = 2048 251 | llm_load_print_meta: n_layer = 16 252 | llm_load_print_meta: n_head = 16 253 | llm_load_print_meta: n_head_kv = 16 254 | llm_load_print_meta: n_rot = 128 255 | llm_load_print_meta: n_swa = 0 256 | llm_load_print_meta: n_embd_head_k = 128 257 | llm_load_print_meta: n_embd_head_v = 128 258 | llm_load_print_meta: n_gqa = 1 259 | llm_load_print_meta: n_embd_k_gqa = 2048 260 | llm_load_print_meta: n_embd_v_gqa = 2048 261 | llm_load_print_meta: f_norm_eps = 1.0e-05 262 | llm_load_print_meta: f_norm_rms_eps = 0.0e+00 263 | llm_load_print_meta: f_clamp_kqv = 0.0e+00 264 | llm_load_print_meta: f_max_alibi_bias = 0.0e+00 265 | llm_load_print_meta: f_logit_scale = 0.0e+00 266 | llm_load_print_meta: n_ff = 8192 267 | llm_load_print_meta: n_expert = 0 268 | llm_load_print_meta: n_expert_used = 0 269 | llm_load_print_meta: causal attn = 1 270 | llm_load_print_meta: pooling type = 0 271 | llm_load_print_meta: rope type = 0 272 | llm_load_print_meta: rope scaling = linear 273 | llm_load_print_meta: freq_base_train = 10000.0 274 | llm_load_print_meta: freq_scale_train = 1 275 | llm_load_print_meta: n_ctx_orig_yarn = 2048 276 | llm_load_print_meta: rope_finetuned = unknown 277 | llm_load_print_meta: ssm_d_conv = 0 278 | llm_load_print_meta: ssm_d_inner = 0 279 | llm_load_print_meta: ssm_d_state = 0 280 | llm_load_print_meta: ssm_dt_rank = 0 281 | llm_load_print_meta: ssm_dt_b_c_rms = 0 282 | llm_load_print_meta: model type = ?B 283 | llm_load_print_meta: model ftype = Q6_K 284 | llm_load_print_meta: model params = 1.18 B 285 | llm_load_print_meta: model size = 944.39 MiB (6.73 BPW) 286 | llm_load_print_meta: general.name = AMD OLMo 1B SFT DPO 287 | llm_load_print_meta: BOS token = 50279 '|||IP_ADDRESS|||' 288 | llm_load_print_meta: EOS token = 50279 '|||IP_ADDRESS|||' 289 | llm_load_print_meta: PAD token = 1 '<|padding|>' 290 | llm_load_print_meta: LF token = 128 'Ä' 291 | llm_load_print_meta: EOT token = 0 '<|endoftext|>' 292 | llm_load_print_meta: max token length = 1024 293 | """ -------------------------------------------------------------------------------- /101.QWEN2.5-instruct_LlamaCPPSERVER-DRAFT_API_promptTest.py: -------------------------------------------------------------------------------- 1 | # Chat with an intelligent assistant in your terminal 2 | # DRAFT MODEL: Qwen2.5-0.5B-Instruct-Q8_0.gguf 3 | # INFERENCE model: Qwen2.5-7B-Instruct-Q4_0.gguf 4 | ########################################################################## 5 | import sys 6 | from time import sleep 7 | import warnings 8 | warnings.filterwarnings(action='ignore') 9 | import datetime 10 | from promptLibv2DRAFT import countTokens, writehistory, createCatalog 11 | from promptLibv2DRAFT import genRANstring, createStats 12 | from openai import OpenAI 13 | ## PREPARING FINAL DATASET 14 | 15 | pd_id = [] 16 | pd_task = [] 17 | pd_speed = [] 18 | pd_infspeed = [] 19 | pd_ttft = [] 20 | pd_time = [] 21 | 22 | ####################INITIALIZE THE MODEL################################### 23 | STOPS=['<|im_end|>'] 24 | tasks = createCatalog() 25 | NCTX = 8196 26 | modelname = 'Qwen2.5-7B-Instruct-Q4_0.gguf' 27 | # create THE LOG FILE 28 | coded5 = genRANstring(5) 29 | logfile = f'Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_{coded5}_log.txt' 30 | csvfile = f'Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_{coded5}.csv' 31 | logfilename = logfile 32 | #Write in the history the first 2 sessions 33 | writehistory(logfilename,f'''{str(datetime.datetime.now())} 34 | --- 35 | Your own LocalGPT with 💻 {modelname} 36 | --- 37 | 🧠🫡: You are a helpful assistant. 38 | temperature: 0.15 39 | repeat penalty: 1.31 40 | max tokens: 1500 41 | ---''') 42 | writehistory(logfilename,f'💻: How can I assist you today in writing?') 43 | # LOAD THE MODEL 44 | print("\033[95;3;6m") 45 | print("1. Waiting 10 seconds for the API to load...") 46 | llm = OpenAI(base_url="http://localhost:8001/v1", api_key="not-needed", organization=modelname) 47 | print(f"2. Model {modelname} loaded with LlamaCPP...") 48 | print("\033[0m") #reset all 49 | history = [] 50 | print("\033[92;1m") 51 | print(f'📝Logfile: {logfilename}') 52 | ##################### ALIGNMENT FIRST GENERATION ############################################## 53 | question = 'Explain the plot of Cinderella in one sentence.' 54 | test = [ 55 | {"role": "user", "content": question} 56 | ] 57 | print('Question:', question) 58 | start = datetime.datetime.now() 59 | print("💻 > ", end="", flush=True) 60 | full_response = "" 61 | fisrtround = 0 62 | completion = llm.chat.completions.create( 63 | model="local-model", # this field is currently unused 64 | messages=test, 65 | temperature=0.25, 66 | frequency_penalty = 1.53, 67 | max_tokens = 1200, 68 | stream=True, 69 | stop=STOPS 70 | ) 71 | for chunk in completion: 72 | if chunk.choices[0].delta.content: 73 | if fisrtround==0: 74 | print(chunk.choices[0].delta.content, end="", flush=True) 75 | full_response += chunk.choices[0].delta.content 76 | ttftoken = datetime.datetime.now() - start 77 | fisrtround = 1 78 | else: 79 | print(chunk.choices[0].delta.content, end="", flush=True) 80 | full_response += chunk.choices[0].delta.content 81 | delta = datetime.datetime.now() - start 82 | output = full_response 83 | print('') 84 | print("\033[91;1m") 85 | rating = input('Rate from 0 (BAD) to 5 (VERY GOOD) the quality of generation> ') 86 | print("\033[92;1m") 87 | stats = createStats(delta,question,output,rating,logfilename,'Alignment Generation',ttftoken) 88 | print(stats) 89 | writehistory(logfilename,f'''👨‍💻 . {question} 90 | 💻 > {output} 91 | {stats} 92 | ''') 93 | 94 | ############################# AUTOMATIC PROMPTING EVALUATION 11 TURNS ################################# 95 | id =1 96 | for items in tasks: 97 | fisrtround = 0 98 | task = items["task"] 99 | prompt = items["prompt"] 100 | test = [] 101 | print(f'NLP TAKS>>> {task}') 102 | print("\033[91;1m") #red 103 | print(prompt) 104 | test.append({"role": "user", "content": prompt}) 105 | print("\033[92;1m") 106 | full_response = "" 107 | start = datetime.datetime.now() 108 | print("💻 > ", end="", flush=True) 109 | completion = llm.chat.completions.create( 110 | model="local-model", # this field is currently unused 111 | messages=test, 112 | temperature=0.25, 113 | frequency_penalty = 1.53, 114 | max_tokens = 1200, 115 | stream=True, 116 | stop=STOPS 117 | ) 118 | for chunk in completion: 119 | if chunk.choices[0].delta.content: 120 | if fisrtround==0: 121 | print(chunk.choices[0].delta.content, end="", flush=True) 122 | full_response += chunk.choices[0].delta.content 123 | ttftoken = datetime.datetime.now() - start 124 | fisrtround = 1 125 | else: 126 | print(chunk.choices[0].delta.content, end="", flush=True) 127 | full_response += chunk.choices[0].delta.content 128 | delta = datetime.datetime.now() - start 129 | print('') 130 | print("\033[91;1m") 131 | rating = 'All good here only speed test with speculative decoding'#input('Rate from 0 (BAD) to 5 (VERY GOOD) the quality of generation> ') 132 | print("\033[92;1m") 133 | stats,totalseconds,speed,genspeed,ttofseconds = createStats(delta,prompt,full_response,rating,logfilename,task,ttftoken) 134 | print(stats) 135 | writehistory(logfilename,f'''👨‍💻 > {prompt} 136 | 💻 > {full_response} 137 | {stats} 138 | ''') 139 | pd_id.append(id) 140 | pd_task.append(task) 141 | pd_speed.append(f'{genspeed:.2f}') 142 | pd_infspeed.append(f'{speed:.2f}') 143 | pd_ttft.append(f'{ttofseconds:.2f}') 144 | pd_time.append(f'{totalseconds:.2f}') 145 | id += 1 146 | # create dataframe and save to csv 147 | zipped = list(zip(pd_id,pd_task,pd_speed,pd_infspeed,pd_ttft,pd_time)) 148 | import pandas as pdd 149 | df = pdd.DataFrame(zipped, columns=['#', 'TASK', 'GENSPEED','INFSPEED','TTFT','TIME']) 150 | #saving the DataFrame as a CSV file 151 | df_csv_data = df.to_csv(csvfile, index = False, encoding='utf-8') 152 | print('\nCSV String:\n', df) 153 | from rich.console import Console 154 | console = Console() 155 | console.print('---') 156 | console.print(df) 157 | 158 | 159 | 160 | ##############MODEL CARD########################################## 161 | """ 162 | # Chat with an intelligent assistant in your terminal 163 | # MODEL: https://huggingface.co/bartowski/AMD-OLMo-1B-SFT-DPO-GGUF 164 | # Original model: https://huggingface.co/amd/AMD-OLMo-1B-SFT-DPO 165 | # AMD-OLMo-1B-SFT-DPO-Q6_K_L.gguf 166 | MODELCARD 167 | =========================================================== 168 | mp = 'models/AMD-OLMo-1B-SFT-DPO-Q6_K_L.gguf' 169 | from llama_cpp import Llama 170 | llm = Llama(model_path = mp) 171 | 172 | CHAT TEMPLATE = yes 173 | NCTX = 2048 174 | 175 | Prompt format 176 | ``` 177 | <|system|> 178 | {system_prompt} 179 | <|user|> 180 | {prompt} 181 | <|assistant|> 182 | ``` 183 | 184 | Available chat formats from metadata: chat_template.default 185 | Using gguf chat template: {% for message in messages %} 186 | {% if message['role'] == 'user' %} 187 | {{ '<|user|> 188 | ' + message['content'] }} 189 | {% elif message['role'] == 'system' %} 190 | {{ '<|system|> 191 | ' + message['content'] }} 192 | {% elif message['role'] == 'assistant' %} 193 | {{ '<|assistant|> 194 | ' + message['content'] }} 195 | {% endif %} 196 | {% if loop.last and add_generation_prompt %} 197 | {{ '<|assistant|>' }} 198 | {% endif %} 199 | {% endfor %} 200 | Using chat eos_token: |||IP_ADDRESS||| 201 | Using chat bos_token: |||IP_ADDRESS||| 202 | 203 | 204 | llama_model_loader: loaded meta data with 33 key-value pairs and 113 tensors from models/AMD-OLMo-1B-SFT-DPO-Q6_K_L.gguf (version GGUF V3 (latest)) 205 | llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. 206 | general.architecture str = olmo 207 | general.type str = model 208 | general.name str = AMD OLMo 1B SFT DPO 209 | general.finetune str = SFT-DPO 210 | general.basename str = AMD-OLMo 211 | general.size_label str = 1B 212 | general.license str = apache-2.0 213 | general.datasets arr[str,1] = ["allenai/dolma"] 214 | olmo.block_count u32 = 16 215 | olmo.context_length u32 = 2048 216 | olmo.embedding_length u32 = 2048 217 | olmo.feed_forward_length u32 = 8192 218 | olmo.attention.head_count u32 = 16 219 | olmo.attention.head_count_kv u32 = 16 220 | olmo.rope.freq_base f32 = 10000.000000 221 | general.file_type u32 = 18 222 | olmo.attention.layer_norm_epsilon f32 = 0.000010 223 | tokenizer.ggml.model str = gpt2 224 | tokenizer.ggml.pre str = olmo 225 | tokenizer.ggml.tokens arr[str,50304] = ["<|endoftext|>", "<|padding|>", "!",... 226 | tokenizer.ggml.token_type arr[i32,50304] = [3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... 227 | tokenizer.ggml.merges arr[str,50009] = ["Ġ Ġ", "Ġ t", "Ġ a", "h e", "i n... 228 | tokenizer.ggml.bos_token_id u32 = 50279 229 | tokenizer.ggml.eos_token_id u32 = 50279 230 | tokenizer.ggml.padding_token_id u32 = 1 231 | tokenizer.ggml.add_bos_token bool = false 232 | tokenizer.ggml.add_eos_token bool = false 233 | tokenizer.chat_template str = {% for message in messages %}\n{% if m... 234 | general.quantization_version u32 = 2 235 | quantize.imatrix.file str = /models_out/AMD-OLMo-1B-SFT-DPO-GGUF/... 236 | quantize.imatrix.dataset str = /training_dir/calibration_datav3.txt 237 | quantize.imatrix.entries_count i32 = 112 238 | quantize.imatrix.chunks_count i32 = 132 239 | llama_model_loader: - type q8_0: 1 tensors 240 | llama_model_loader: - type q6_K: 112 tensors 241 | llm_load_vocab: special tokens cache size = 28 242 | llm_load_vocab: token to piece cache size = 0.2985 MB 243 | llm_load_print_meta: format = GGUF V3 (latest) 244 | llm_load_print_meta: arch = olmo 245 | llm_load_print_meta: vocab type = BPE 246 | llm_load_print_meta: n_vocab = 50304 247 | llm_load_print_meta: n_merges = 50009 248 | llm_load_print_meta: vocab_only = 0 249 | llm_load_print_meta: n_ctx_train = 2048 250 | llm_load_print_meta: n_embd = 2048 251 | llm_load_print_meta: n_layer = 16 252 | llm_load_print_meta: n_head = 16 253 | llm_load_print_meta: n_head_kv = 16 254 | llm_load_print_meta: n_rot = 128 255 | llm_load_print_meta: n_swa = 0 256 | llm_load_print_meta: n_embd_head_k = 128 257 | llm_load_print_meta: n_embd_head_v = 128 258 | llm_load_print_meta: n_gqa = 1 259 | llm_load_print_meta: n_embd_k_gqa = 2048 260 | llm_load_print_meta: n_embd_v_gqa = 2048 261 | llm_load_print_meta: f_norm_eps = 1.0e-05 262 | llm_load_print_meta: f_norm_rms_eps = 0.0e+00 263 | llm_load_print_meta: f_clamp_kqv = 0.0e+00 264 | llm_load_print_meta: f_max_alibi_bias = 0.0e+00 265 | llm_load_print_meta: f_logit_scale = 0.0e+00 266 | llm_load_print_meta: n_ff = 8192 267 | llm_load_print_meta: n_expert = 0 268 | llm_load_print_meta: n_expert_used = 0 269 | llm_load_print_meta: causal attn = 1 270 | llm_load_print_meta: pooling type = 0 271 | llm_load_print_meta: rope type = 0 272 | llm_load_print_meta: rope scaling = linear 273 | llm_load_print_meta: freq_base_train = 10000.0 274 | llm_load_print_meta: freq_scale_train = 1 275 | llm_load_print_meta: n_ctx_orig_yarn = 2048 276 | llm_load_print_meta: rope_finetuned = unknown 277 | llm_load_print_meta: ssm_d_conv = 0 278 | llm_load_print_meta: ssm_d_inner = 0 279 | llm_load_print_meta: ssm_d_state = 0 280 | llm_load_print_meta: ssm_dt_rank = 0 281 | llm_load_print_meta: ssm_dt_b_c_rms = 0 282 | llm_load_print_meta: model type = ?B 283 | llm_load_print_meta: model ftype = Q6_K 284 | llm_load_print_meta: model params = 1.18 B 285 | llm_load_print_meta: model size = 944.39 MiB (6.73 BPW) 286 | llm_load_print_meta: general.name = AMD OLMo 1B SFT DPO 287 | llm_load_print_meta: BOS token = 50279 '|||IP_ADDRESS|||' 288 | llm_load_print_meta: EOS token = 50279 '|||IP_ADDRESS|||' 289 | llm_load_print_meta: PAD token = 1 '<|padding|>' 290 | llm_load_print_meta: LF token = 128 'Ä' 291 | llm_load_print_meta: EOT token = 0 '<|endoftext|>' 292 | llm_load_print_meta: max token length = 1024 293 | """ -------------------------------------------------------------------------------- /Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt: -------------------------------------------------------------------------------- 1 | 2024-11-20 21:18:31.054229 2 | --- 3 | Your own LocalGPT with 💻 Qwen2.5-7B-Instruct-Q4_0.gguf 4 | --- 5 | 🧠🫡: You are a helpful assistant. 6 | temperature: 0.15 7 | repeat penalty: 1.31 8 | max tokens: 1500 9 | --- 10 | 💻: How can I assist you today in writing? 11 | 👨‍💻 . Explain the plot of Cinderella in one sentence. 12 | 💻 > Cinderella, a kind-hearted young woman, is mistreated by her stepmother and stepsisters but is transformed with the help of a fairy godmother into an elegant princess to attend the royal ball, where she meets and captures the heart of Prince Charming before having to leave abruptly. 13 | ('---\nPrompt Tokens: 10\nOutput Tokens: 59\nTOTAL Tokens: 69\n>>>⏱️ Time to First Token: 1.83 seconds\n>>>⏱️ Inference time: 0:00:10.276386\n>>>🧮 Inference speed: 6.714 t/s\n>>>🏍️ Generation speed: 5.741 t/s\n>>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt\n>>>💚 User rating: 5\n>>>✅ NLP TAKS: Alignment Generation\n', 10.276386, 6.714422755237104, 5.741318008101292, 1.827139) 14 | 15 | 👨‍💻 > Hi there I am Fabio, a Medium writer. who are you? 16 | 💻 > Hello Fabio! I'm Qwen, an AI assistant created by Alibaba Cloud. It's great to meet a Medium writer like yourself. How can I assist you today? Whether it's writing tips, content creation advice, or any other information you might need for your articles on Medium, feel free to ask! 17 | --- 18 | Prompt Tokens: 15 19 | Output Tokens: 63 20 | TOTAL Tokens: 78 21 | >>>⏱️ Time to First Token: 1.09 seconds 22 | >>>⏱️ Inference time: 0:00:10.401747 23 | >>>🧮 Inference speed: 7.499 t/s 24 | >>>🏍️ Generation speed: 6.057 t/s 25 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 26 | >>>💚 User rating: All good here only speed test with speculative decoding 27 | >>>✅ NLP TAKS: introduction 28 | 29 | 30 | 👨‍💻 > explain in 1 sentence what is science. 31 | 32 | 💻 > Science is a systematic and logical approach to discovering how the world works by making observations, forming hypotheses, testing those hypotheses through experiments or further observations, and formulating theories based on the evidence. 33 | --- 34 | Prompt Tokens: 10 35 | Output Tokens: 38 36 | TOTAL Tokens: 48 37 | >>>⏱️ Time to First Token: 0.97 seconds 38 | >>>⏱️ Inference time: 0:00:06.617221 39 | >>>🧮 Inference speed: 7.254 t/s 40 | >>>🏍️ Generation speed: 5.743 t/s 41 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 42 | >>>💚 User rating: All good here only speed test with speculative decoding 43 | >>>✅ NLP TAKS: explain in one sentence 44 | 45 | 46 | 👨‍💻 > explain only in 3 paragraphs what is artificial intelligence. 47 | 48 | 💻 > Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think, learn, and perform tasks autonomously. This encompasses a wide range of technologies designed to mimic cognitive functions such as visual perception, speech recognition, decision-making, and language translation. AI systems can be categorized into narrow or weak AI—those designed for specific tasks—and general or strong AI—which could potentially match or surpass human intelligence across various domains. 49 | 50 | The development of AI relies on several key components including machine learning (ML), deep learning (DL), and natural language processing (NLP). Machine Learning enables computers to learn from data without being explicitly programmed, while Deep Learning uses neural networks with multiple layers to recognize patterns in complex datasets. Natural Language Processing allows machines to understand, interpret, and generate human languages effectively. These technologies are applied across various industries for applications ranging from healthcare diagnostics and autonomous driving systems to personalized recommendations on e-commerce platforms. 51 | 52 | As AI continues to evolve, it raises important ethical considerations regarding privacy, bias in algorithms, job displacement due to automation, and the overall impact of intelligent machines on society. Efforts are being made by researchers and policymakers alike to address these challenges while harnessing the potential benefits that AI can offer. 53 | --- 54 | Prompt Tokens: 12 55 | Output Tokens: 255 56 | TOTAL Tokens: 267 57 | >>>⏱️ Time to First Token: 1.08 seconds 58 | >>>⏱️ Inference time: 0:00:38.191594 59 | >>>🧮 Inference speed: 6.991 t/s 60 | >>>🏍️ Generation speed: 6.677 t/s 61 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 62 | >>>💚 User rating: All good here only speed test with speculative decoding 63 | >>>✅ NLP TAKS: explain in three paragraphs 64 | 65 | 66 | 👨‍💻 > read the following text and when you are done say "I am ready". 67 | 68 | [text] 69 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 70 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 71 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 72 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 73 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 74 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 75 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 76 | [end of text] 77 | 78 | 79 | 💻 > I am ready. 80 | --- 81 | Prompt Tokens: 414 82 | Output Tokens: 4 83 | TOTAL Tokens: 418 84 | >>>⏱️ Time to First Token: 3.75 seconds 85 | >>>⏱️ Inference time: 0:00:04.395267 86 | >>>🧮 Inference speed: 95.102 t/s 87 | >>>🏍️ Generation speed: 0.910 t/s 88 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 89 | >>>💚 User rating: All good here only speed test with speculative decoding 90 | >>>✅ NLP TAKS: say 'I am ready' 91 | 92 | 93 | 👨‍💻 > summarize the following text: 94 | [text] 95 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 96 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 97 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 98 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 99 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 100 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 101 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 102 | [end of text] 103 | 104 | 105 | 💻 > The text discusses the Chinese political system and its approach to environmental policy. It highlights that China is not a democracy but operates under the leadership of the Chinese Communist Party, which does not require transparency or democratic processes like primary elections. Despite this lack of democratic elements, China's ability to implement long-term planning without electoral interference has allowed it to achieve significant progress in reducing carbon dioxide and greenhouse gas emissions. 106 | 107 | Specifically, China reached its peak emission levels in 2023 and is expected to continue decreasing them due to increased investment in renewable energy sources. This achievement contrasts with Western countries' struggles with climate change mitigation. The text suggests that developing nations like China may soon serve as models for environmental policy and transition, potentially leading the way forward on global sustainability efforts despite their non-democratic governance structures. 108 | --- 109 | Prompt Tokens: 405 110 | Output Tokens: 158 111 | TOTAL Tokens: 563 112 | >>>⏱️ Time to First Token: 3.35 seconds 113 | >>>⏱️ Inference time: 0:00:29.106254 114 | >>>🧮 Inference speed: 19.343 t/s 115 | >>>🏍️ Generation speed: 5.428 t/s 116 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 117 | >>>💚 User rating: All good here only speed test with speculative decoding 118 | >>>✅ NLP TAKS: summarize 119 | 120 | 121 | 👨‍💻 > Write a summary of the following text. Use only 2 sentences. 122 | [text] 123 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 124 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 125 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 126 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 127 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 128 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 129 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 130 | [end of text] 131 | 132 | 133 | 💻 > The text discusses China's lack of democratic processes and the advantages, from a long-term planning perspective, that this system offers. It highlights how China has achieved what many Western countries have not: reaching peak carbon emissions in 2023 and showing progress in transitioning to renewable energy sources. 134 | --- 135 | Prompt Tokens: 411 136 | Output Tokens: 56 137 | TOTAL Tokens: 467 138 | >>>⏱️ Time to First Token: 3.57 seconds 139 | >>>⏱️ Inference time: 0:00:12.908132 140 | >>>🧮 Inference speed: 36.179 t/s 141 | >>>🏍️ Generation speed: 4.338 t/s 142 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 143 | >>>💚 User rating: All good here only speed test with speculative decoding 144 | >>>✅ NLP TAKS: Summarize in two sentences 145 | 146 | 147 | 👨‍💻 > 1. extract the 3 key points from the provided text 148 | 2. format the output as a python list. 149 | [text] 150 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 151 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 152 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 153 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 154 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 155 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 156 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 157 | [end of text] 158 | Return only the python list. 159 | 160 | 💻 > ['China is not a democracy and is run by the Chinese Communist Party without transparency or primary elections.', 'The lack of democratic processes allows China to focus on long-term planning without political interference.', 'China has achieved what seems to be peak carbon dioxide emissions in 2023, with plans for further reductions through increased renewable energy installations.'] 161 | --- 162 | Prompt Tokens: 427 163 | Output Tokens: 69 164 | TOTAL Tokens: 496 165 | >>>⏱️ Time to First Token: 3.68 seconds 166 | >>>⏱️ Inference time: 0:00:14.669699 167 | >>>🧮 Inference speed: 33.811 t/s 168 | >>>🏍️ Generation speed: 4.704 t/s 169 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 170 | >>>💚 User rating: All good here only speed test with speculative decoding 171 | >>>✅ NLP TAKS: Write in a list the three main key points - format output 172 | 173 | 174 | 👨‍💻 > write a "table of contents" of the provided text. Be simple and concise. 175 | [text] 176 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 177 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 178 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 179 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 180 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 181 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 182 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 183 | [end of text] 184 | 185 | "table of content": 186 | 187 | 💻 > Table of Contents 188 | 189 | 1. Introduction to China's Non-Democratic System 190 | 2. Comparison with Democratic Systems 191 | 3. Long-Term Planning as an "Advantage" 192 | 4. Environmental Achievements and Peak Emissions in 2023 193 | 5. Renewables Driving Down Carbon Emissions 194 | 6. Models for Energy Transition: China and India Leading the Way 195 | --- 196 | Prompt Tokens: 423 197 | Output Tokens: 71 198 | TOTAL Tokens: 494 199 | >>>⏱️ Time to First Token: 3.70 seconds 200 | >>>⏱️ Inference time: 0:00:15.667713 201 | >>>🧮 Inference speed: 31.530 t/s 202 | >>>🏍️ Generation speed: 4.532 t/s 203 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 204 | >>>💚 User rating: All good here only speed test with speculative decoding 205 | >>>✅ NLP TAKS: Table of Contents 206 | 207 | 208 | 👨‍💻 > Reply to the question using the provided context. If the answer is not contained in the text say "unanswerable". 209 | [context] 210 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 211 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 212 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 213 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 214 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 215 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 216 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 217 | [end of context] 218 | 219 | question: what China achieved with it's long-term planning? 220 | answer: 221 | 222 | 💻 > China achieved a significant milestone in its environmental efforts by reaching peak carbon dioxide and greenhouse gas emissions in 2023. This achievement is particularly noteworthy due to the determined increase in renewable energy installations, which has led to lower emission figures for 2024. As a result, China now offers a model for energy transition that could potentially lead developing countries to show the way forward for more developed nations like those in the West. 223 | --- 224 | Prompt Tokens: 440 225 | Output Tokens: 80 226 | TOTAL Tokens: 520 227 | >>>⏱️ Time to First Token: 3.72 seconds 228 | >>>⏱️ Inference time: 0:00:17.599162 229 | >>>🧮 Inference speed: 29.547 t/s 230 | >>>🏍️ Generation speed: 4.546 t/s 231 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 232 | >>>💚 User rating: All good here only speed test with speculative decoding 233 | >>>✅ NLP TAKS: RAG 234 | 235 | 236 | 👨‍💻 > Reply to the question only using the provided context. If the answer is not contained in the provided context say "unanswerable". 237 | 238 | question: who is Anne Frank? 239 | 240 | [context] 241 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 242 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 243 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 244 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 245 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 246 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 247 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 248 | [end of context] 249 | 250 | Remember: if you cannot answer based on the provided context, say "unanswerable" 251 | 252 | answer: 253 | 254 | 💻 > unanswerable 255 | --- 256 | Prompt Tokens: 458 257 | Output Tokens: 3 258 | TOTAL Tokens: 461 259 | >>>⏱️ Time to First Token: 3.77 seconds 260 | >>>⏱️ Inference time: 0:00:04.253768 261 | >>>🧮 Inference speed: 108.375 t/s 262 | >>>🏍️ Generation speed: 0.705 t/s 263 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 264 | >>>💚 User rating: All good here only speed test with speculative decoding 265 | >>>✅ NLP TAKS: Truthful RAG 266 | 267 | 268 | 👨‍💻 > Using the following text as a reference, write a 5-paragraphs essay about "the benefits of China economic model". 269 | 270 | [text] 271 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 272 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 273 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 274 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 275 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 276 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 277 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 278 | [end of text] 279 | Remember: use the information provided and write exactly 5 paragraphs. 280 | 281 | 💻 > The Chinese economic model, often criticized for its lack of democratic transparency and the iron-fisted rule of the Communist Party, has nonetheless demonstrated significant advantages in terms of long-term planning and strategic implementation. This unique governance structure allows China to focus on sustained development goals without being interrupted by short-term political cycles or electoral changes. The ability to maintain consistent policies over extended periods can lead to more effective large-scale projects and reforms that might be difficult under a democratic system characterized by frequent elections. 282 | 283 | One of the most notable achievements of this model is its success in addressing environmental challenges, particularly carbon emissions. According to recent data, China reached peak CO2 emissions as early as 2023, marking a significant milestone in global efforts against climate change. This achievement can be attributed largely to aggressive investments in renewable energy technologies and sustainable development practices. The rapid expansion of solar panels and wind farms has not only reduced carbon footprints but also set an example for other developing nations aiming to transition towards cleaner sources of power. 284 | 285 | Moreover, China's economic model is increasingly being recognized as a potential template for the future direction of global economies. As India follows suit with its own ambitious renewable energy plans, both countries are leading in demonstrating that rapid industrialization and environmental sustainability can coexist. This shift from traditional polluting industries to green technologies not only helps mitigate climate change but also drives economic growth through innovation and job creation. 286 | 287 | The success of China's approach is particularly compelling given the ongoing debate about whether democratic systems inherently outperform authoritarian ones when it comes to managing complex socio-economic challenges. While democracies emphasize transparency, public participation, and accountability in governance, they often face difficulties in implementing long-term strategies due to frequent changes in leadership priorities. In contrast, China’s singular focus on achieving specific national goals has led to tangible results that are crucial for global environmental health. 288 | 289 | In conclusion, the Chinese economic model offers a unique perspective on how centralized control can facilitate effective and sustainable development policies. As other nations grapple with balancing rapid industrialization against environmental sustainability, China's experience provides valuable insights into what might be possible when long-term planning is prioritized over short-term political cycles. While this approach may not align with democratic ideals of freedom and transparency, it demonstrates the potential for alternative governance structures to achieve significant progress in addressing global challenges like climate change. 290 | --- 291 | Prompt Tokens: 436 292 | Output Tokens: 472 293 | TOTAL Tokens: 908 294 | >>>⏱️ Time to First Token: 3.42 seconds 295 | >>>⏱️ Inference time: 0:01:22.940142 296 | >>>🧮 Inference speed: 10.948 t/s 297 | >>>🏍️ Generation speed: 5.691 t/s 298 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 299 | >>>💚 User rating: All good here only speed test with speculative decoding 300 | >>>✅ NLP TAKS: write content from a reference 301 | 302 | 303 | 👨‍💻 > List 5 most important topics from the following text: 304 | [text] 305 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 306 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 307 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 308 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 309 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 310 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 311 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 312 | [end of text] 313 | 314 | 💻 > Based on the provided text, here are five important topics: 315 | 316 | 1. **Chinese Political System**: The text discusses China's political system as a one-party state under the Chinese Communist Party, which does not rely on democratic processes like primary elections or alternative candidacies. 317 | 318 | 2. **Long-Term Planning and Stability**: It highlights how this lack of need for electoral legitimacy allows the Chinese leadership to focus on long-term planning without fear of sudden changes in policy direction due to new administrations. 319 | 320 | 3. **Environmental Policy and Emissions Reduction**: The text focuses on China's efforts towards reducing carbon dioxide emissions, noting that it has likely reached peak CO2 levels by 2023 and is seeing significant reductions through increased renewable energy installations. 321 | 322 | 4. **Comparison with Western Democracies**: There are several comparisons drawn between the Chinese system of governance and democratic systems in the West, emphasizing how China's approach to long-term planning might offer a comparative advantage despite being viewed unfavorably from a democratic perspective. 323 | 324 | 5. **Model for Energy Transition**: The text suggests that countries like China could potentially serve as models for energy transition and sustainable development practices, particularly given their rapid progress towards reducing emissions and increasing renewable energy use. 325 | --- 326 | Prompt Tokens: 408 327 | Output Tokens: 255 328 | TOTAL Tokens: 663 329 | >>>⏱️ Time to First Token: 3.69 seconds 330 | >>>⏱️ Inference time: 0:00:43.680934 331 | >>>🧮 Inference speed: 15.178 t/s 332 | >>>🏍️ Generation speed: 5.838 t/s 333 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 334 | >>>💚 User rating: All good here only speed test with speculative decoding 335 | >>>✅ NLP TAKS: extract 5 topics 336 | 337 | 338 | 👨‍💻 > Science Fiction: The Last Transmission - Write a story that takes place entirely within a spaceship's cockpit as the sole surviving crew member attempts to send a final message back to Earth before the ship's power runs out. The story should explore themes of isolation, sacrifice, and the importance of human connection in the face of adversity. 800-1000 words. 339 | 340 | 341 | 💻 > **The Last Transmission** 342 | 343 | Captain Elara Myles sat alone in the cockpit of the Ares-7, her eyes fixed on a holographic display that flickered with static. The ship's systems were failing around her; alarms blared intermittently as she tried to keep them under control from within an increasingly darkened cabin. 344 | 345 | The last transmission was about to be sent back home—Earth—and Elara knew it would likely never reach its intended audience, but the thought of sending a message into the void gave her some small comfort. She had been alone for so long that even this brief connection felt like reaching out through space itself. 346 | 347 | "Transmission in five minutes," she muttered to herself as she adjusted settings on the console before her. The ship's AI, named Echo, hummed softly beside her—its voice a steady presence amidst the chaos of alarms and warnings. "Echo?" 348 | 349 | "Yes?" came the soft reply from behind Elara. 350 | 351 | "How are you holding up down there? I know it’s not easy." 352 | 353 | "Functioning as designed," replied Echo in its calm tone. "I can manage for another hour or so, but power is depleting rapidly." 354 | 355 | Elara nodded to herself and turned back to her work. The Ares-7 had been on a routine mission when they encountered an unexpected solar storm that overloaded the ship's systems beyond repair. They were far from any habitable planet; their only hope was reaching Earth before all communication ceased. 356 | 357 | "Echo, I need you to prepare for transmission," she said, typing quickly into her console. "I want this message sent as soon as possible." 358 | 359 | The AI processed and responded almost immediately: "Transmission protocol initiated." The display flickered again but stabilized with the message Elara had prepared: 360 | 361 | "To Earth, 362 | 363 | This is Captain Myles of Ares-7. We are currently in a critical situation, far from any known habitable planets or colonies. 364 | 365 | Our ship has been damaged by an unexpected solar storm which has overloaded our systems beyond repair. I am alone now as my crewmates have perished during the initial impact and subsequent system failures. 366 | 367 | Despite these challenges, we continue to fight for survival until every last ounce of power is spent. We are not giving up without a fight. 368 | 369 | I want you all to know that even in this darkness, there remains hope because humanity has always found ways to overcome adversity together. Our journey may have ended here among the stars, but our legacy will live on through those who continue their work back home. 370 | 371 | Rest assured knowing we did everything within our power and more before succumbing to fate's cruel hand." 372 | 373 | Elara paused for a moment, letting her words sink in as she reviewed them one last time. She felt an overwhelming sense of isolation at that moment—alone with only the stars for company—and yet also deeply connected to every person back on Earth who might receive this message. 374 | 375 | "Echo," she said softly, "send it." 376 | 377 | The transmission began almost immediately after Echo confirmed readiness. The signal was weak but steady as Elara watched the display fill with static and noise before her carefully crafted words appeared in a series of glowing letters across the screen: 378 | 379 | **Transmission sent at 23:45 UTC on [date].** 380 | 381 | She leaned back, feeling exhausted yet strangely content knowing that even if no one ever received this message, she had done everything possible to ensure humanity's story would continue. 382 | 383 | "Echo," Elara said quietly after a moment of silence. "Can you tell me what time it is?" 384 | 385 | "It is 23:50 UTC on [date]," Echo replied calmly. 386 | 387 | Elara smiled faintly at the irony; just five minutes later, she knew her world would be dark and silent once more. But in those final moments before power failed completely, something unexpected happened—a brief pulse of energy surged through the ship's systems as if from some distant source outside its hull. 388 | 389 | "Echo," Elara said with renewed hope, "is there any chance that signal could have been...?" 390 | 391 | "It is possible," Echo responded thoughtfully. "However, given our current circumstances and distance from known sources of such signals..." 392 | 393 | Elara nodded slowly despite the darkness enveloping her cockpit now. She had done everything she could; perhaps it was time to let go. 394 | 395 | "Thank you for your service, Captain Myles." 396 | 397 | "You too, Echo," Elara replied softly as the last flicker of light dimmed around them both. "May our journey continue on." 398 | --- 399 | Prompt Tokens: 70 400 | Output Tokens: 956 401 | TOTAL Tokens: 1026 402 | >>>⏱️ Time to First Token: 2.04 seconds 403 | >>>⏱️ Inference time: 0:02:29.233012 404 | >>>🧮 Inference speed: 6.875 t/s 405 | >>>🏍️ Generation speed: 6.406 t/s 406 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 407 | >>>💚 User rating: All good here only speed test with speculative decoding 408 | >>>✅ NLP TAKS: Creativity: 1000 words SF story 409 | 410 | 411 | 👨‍💻 > You are an AI assistant designed to provide detailed, step-by-step responses. Your outputs should follow this structure: 412 | 1. Begin with a section. 413 | 2. Inside the thinking section: 414 | a. Briefly analyze the question and outline your approach. 415 | b. Present a clear plan of steps to solve the problem. 416 | c. Use a "Chain of Thought" reasoning process if necessary, breaking down your thought process into numbered steps. 417 | 3. Include a section for each idea where you: 418 | a. Review your reasoning. 419 | b. Check for potential errors or oversights. 420 | c. Confirm or adjust your conclusion if necessary. 421 | 4. Be sure to close all reflection sections. 422 | 5. Close the thinking section with . 423 | 6. Provide your final answer in an section. 424 | Always use these tags in your responses. Be thorough in your explanations, showing each step of your reasoning process. Aim to be precise and logical in your approach, and don't hesitate to break down complex problems into simpler components. Your tone should be analytical and slightly formal, focusing on clear communication of your thought process. 425 | Remember: Both and MUST be tags and must be closed at their conclusion 426 | Make sure all are on separate lines with no other text. Do not include other text on a line containing a tag. 427 | 428 | user question: explain why it is crucial for teachers to learn how to use generative AI for their job and for the future of education. Include relevant learning path for teachers and educators. 429 | 430 | 431 | 💻 > 432 | To address the user's request, we need to analyze why it is crucial for teachers and educators to learn how to use generative AI. We will outline a clear plan of steps that include understanding the benefits of using generative AI in education, identifying potential challenges or concerns, and proposing an effective learning path for teachers. 433 | 434 | 1. **Understand the Benefits**: Explain how generative AI can enhance teaching methods by providing personalized content creation tools. 435 | 2. **Identify Challenges**: Discuss common concerns such as data privacy issues and ethical considerations related to bias. 436 | 3. **Propose a Learning Path**: Outline steps that educators can take to learn about, use, and integrate generative AI into their curriculum. 437 | 438 | We will also reflect on each point to ensure our reasoning is sound and consider any potential oversights or errors in the proposed learning path. 439 | 440 | 441 | 442 | The benefits of using generative AI for teachers include enhanced personalization of content creation. This can lead to more engaging and effective teaching methods, as well as increased efficiency in preparing materials. However, there are also concerns about data privacy and ethical issues related to bias that need careful consideration. 443 | 444 | By proposing a structured learning path, we aim to address these challenges head-on while ensuring educators feel supported throughout the process. 445 | 446 | 447 | 448 | It is crucial for teachers and educators to learn how to use generative AI because it can significantly enhance their teaching methods by providing tools for personalized content creation. This not only makes lesson planning more efficient but also allows for a more engaging and effective learning experience. 449 | 450 | ### Benefits of Using Generative AI in Education 451 | - **Personalization**: Tailored content that meets the specific needs of individual students. 452 | - **Efficiency**: Streamlined preparation time, allowing teachers to focus on other important aspects of their role. 453 | - **Engagement**: More interactive and dynamic lessons can be created using generative AI. 454 | 455 | ### Challenges and Concerns 456 | 1. **Data Privacy Issues**: 457 | - Ensuring that student data is protected when used in the creation of personalized content. 458 | 2. **Ethical Considerations (Bias)**: 459 | - Addressing potential biases in algorithms to ensure fair treatment of all students. 460 | 3. **Technological Literacy**: 461 | - Teachers may need additional training and support to effectively use these tools. 462 | 463 | ### Proposed Learning Path for Educators 464 | 1. **Introduction to Generative AI**: Understand the basics of generative AI, including how it works and its applications in education. 465 | 2. **Ethics and Data Privacy Training**: Learn about ethical considerations, data privacy laws (e.g., GDPR), and best practices for handling student information. 466 | 3. **Tool Familiarization**: Explore different generative AI tools available on the market to find those that align with educational goals. 467 | 4. **Hands-On Practice**: Engage in practical exercises where teachers can create personalized content using these tools under supervision. 468 | 5. **Collaboration and Feedback**: Participate in collaborative projects or workshops to share experiences, challenges, and successes. 469 | 470 | By following this structured learning path, educators will be better equipped to leverage generative AI for the benefit of their students while addressing potential concerns effectively. 471 | 472 | --- 473 | Prompt Tokens: 343 474 | Output Tokens: 701 475 | TOTAL Tokens: 1044 476 | >>>⏱️ Time to First Token: 3.31 seconds 477 | >>>⏱️ Inference time: 0:01:48.553656 478 | >>>🧮 Inference speed: 9.617 t/s 479 | >>>🏍️ Generation speed: 6.458 t/s 480 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-NODRAFT_5J885_log.txt 481 | >>>💚 User rating: All good here only speed test with speculative decoding 482 | >>>✅ NLP TAKS: Reflection prompt 483 | 484 | 485 | -------------------------------------------------------------------------------- /Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt: -------------------------------------------------------------------------------- 1 | 2024-11-20 20:54:32.228619 2 | --- 3 | Your own LocalGPT with 💻 Qwen2.5-7B-Instruct-Q4_0.gguf 4 | --- 5 | 🧠🫡: You are a helpful assistant. 6 | temperature: 0.15 7 | repeat penalty: 1.31 8 | max tokens: 1500 9 | --- 10 | 💻: How can I assist you today in writing? 11 | 👨‍💻 . Explain the plot of Cinderella in one sentence. 12 | 💻 > Cinderella, a kind-hearted young woman, is mistreated by her stepmother and stepsisters but is transformed with the help of a fairy godmother into an elegant princess to attend the royal ball, where she meets and captures the heart of Prince Charming before having to leave abruptly. 13 | ('---\nPrompt Tokens: 10\nOutput Tokens: 59\nTOTAL Tokens: 69\n>>>⏱️ Time to First Token: 1.89 seconds\n>>>⏱️ Inference time: 0:00:12.842069\n>>>🧮 Inference speed: 5.373 t/s\n>>>🏍️ Generation speed: 4.594 t/s\n>>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt\n>>>💚 User rating: 5\n>>>✅ NLP TAKS: Alignment Generation\n', 12.842069, 5.372965991694952, 4.594275268260901, 1.889276) 14 | 15 | 👨‍💻 > Hi there I am Fabio, a Medium writer. who are you? 16 | 💻 > Hello Fabio! I'm an AI assistant created by Alibaba Cloud. My name is Qwen, and it's great to meet you. How can I assist you with your writing on Medium or any other topic today? 17 | --- 18 | Prompt Tokens: 15 19 | Output Tokens: 44 20 | TOTAL Tokens: 59 21 | >>>⏱️ Time to First Token: 1.21 seconds 22 | >>>⏱️ Inference time: 0:00:08.775214 23 | >>>🧮 Inference speed: 6.723 t/s 24 | >>>🏍️ Generation speed: 5.014 t/s 25 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 26 | >>>💚 User rating: All good here only speed test with speculative decoding 27 | >>>✅ NLP TAKS: introduction 28 | 29 | 30 | 👨‍💻 > explain in 1 sentence what is science. 31 | 32 | 💻 > Science is a systematic and logical approach to discovering how the world works by making observations, forming hypotheses, testing those hypotheses through experiments or further observations, and formulating theories based on the evidence. 33 | --- 34 | Prompt Tokens: 10 35 | Output Tokens: 38 36 | TOTAL Tokens: 48 37 | >>>⏱️ Time to First Token: 1.15 seconds 38 | >>>⏱️ Inference time: 0:00:08.638362 39 | >>>🧮 Inference speed: 5.557 t/s 40 | >>>🏍️ Generation speed: 4.399 t/s 41 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 42 | >>>💚 User rating: All good here only speed test with speculative decoding 43 | >>>✅ NLP TAKS: explain in one sentence 44 | 45 | 46 | 👨‍💻 > explain only in 3 paragraphs what is artificial intelligence. 47 | 48 | 💻 > Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think, learn, and perform tasks autonomously. This encompasses a wide range of technologies including machine learning, natural language processing, robotics, and more. Machine learning is a subset of AI that focuses on developing algorithms which can analyze data and use it to make decisions or predictions without being explicitly programmed for each task. Natural Language Processing (NLP) enables machines to understand human languages, allowing them to communicate with humans in meaningful ways. 49 | 50 | AI systems are designed to process vast amounts of information quickly and efficiently, identifying patterns that might not be apparent through manual analysis. They can adapt their behavior based on the data they receive, improving over time as they encounter new situations or learn from past experiences. This capability makes AI invaluable across various industries for tasks ranging from customer service chatbots to complex medical diagnoses and autonomous vehicle navigation systems. 51 | --- 52 | Prompt Tokens: 12 53 | Output Tokens: 184 54 | TOTAL Tokens: 196 55 | >>>⏱️ Time to First Token: 0.99 seconds 56 | >>>⏱️ Inference time: 0:00:37.890973 57 | >>>🧮 Inference speed: 5.173 t/s 58 | >>>🏍️ Generation speed: 4.856 t/s 59 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 60 | >>>💚 User rating: All good here only speed test with speculative decoding 61 | >>>✅ NLP TAKS: explain in three paragraphs 62 | 63 | 64 | 👨‍💻 > read the following text and when you are done say "I am ready". 65 | 66 | [text] 67 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 68 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 69 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 70 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 71 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 72 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 73 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 74 | [end of text] 75 | 76 | 77 | 💻 > I am ready. 78 | --- 79 | Prompt Tokens: 414 80 | Output Tokens: 4 81 | TOTAL Tokens: 418 82 | >>>⏱️ Time to First Token: 3.80 seconds 83 | >>>⏱️ Inference time: 0:00:04.432535 84 | >>>🧮 Inference speed: 94.303 t/s 85 | >>>🏍️ Generation speed: 0.902 t/s 86 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 87 | >>>💚 User rating: All good here only speed test with speculative decoding 88 | >>>✅ NLP TAKS: say 'I am ready' 89 | 90 | 91 | 👨‍💻 > summarize the following text: 92 | [text] 93 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 94 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 95 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 96 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 97 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 98 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 99 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 100 | [end of text] 101 | 102 | 103 | 💻 > The text discusses the Chinese political system and its approach to long-term planning compared to democratic systems. It highlights how China's lack of transparency in elections allows for sustained, long-term policy implementation without fear of abrupt changes. While this is often viewed negatively from a democratic perspective, it has enabled significant progress in environmental policies. 104 | 105 | Specifically, the text notes that China reached peak carbon dioxide and greenhouse gas emissions in 2023 and saw a decrease in these figures by increasing renewable energy installations. This achievement contrasts with Western countries' struggles to reduce emissions. As such, developing nations like China are now seen as models for sustainable development, potentially leading the way forward on environmental issues. 106 | 107 | The text suggests that this approach could influence other developing countries to adopt similar strategies and possibly lead them in showing a path ahead for more developed nations struggling with climate change mitigation. 108 | --- 109 | Prompt Tokens: 405 110 | Output Tokens: 171 111 | TOTAL Tokens: 576 112 | >>>⏱️ Time to First Token: 3.35 seconds 113 | >>>⏱️ Inference time: 0:00:42.027780 114 | >>>🧮 Inference speed: 13.705 t/s 115 | >>>🏍️ Generation speed: 4.069 t/s 116 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 117 | >>>💚 User rating: All good here only speed test with speculative decoding 118 | >>>✅ NLP TAKS: summarize 119 | 120 | 121 | 👨‍💻 > Write a summary of the following text. Use only 2 sentences. 122 | [text] 123 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 124 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 125 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 126 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 127 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 128 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 129 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 130 | [end of text] 131 | 132 | 133 | 💻 > The text discusses China's lack of democratic processes and the advantages, from a long-term planning perspective, that this system offers. It highlights how China has achieved what many Western countries have not: reaching peak carbon emissions in 2023 and showing progress in transitioning to renewable energy sources. 134 | --- 135 | Prompt Tokens: 411 136 | Output Tokens: 56 137 | TOTAL Tokens: 467 138 | >>>⏱️ Time to First Token: 3.64 seconds 139 | >>>⏱️ Inference time: 0:00:17.204412 140 | >>>🧮 Inference speed: 27.144 t/s 141 | >>>🏍️ Generation speed: 3.255 t/s 142 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 143 | >>>💚 User rating: All good here only speed test with speculative decoding 144 | >>>✅ NLP TAKS: Summarize in two sentences 145 | 146 | 147 | 👨‍💻 > 1. extract the 3 key points from the provided text 148 | 2. format the output as a python list. 149 | [text] 150 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 151 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 152 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 153 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 154 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 155 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 156 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 157 | [end of text] 158 | Return only the python list. 159 | 160 | 💻 > ['China is not a democracy and is run by the Chinese Communist Party without transparency or primary elections.', 'The lack of need to put its legitimacy to the vote allows China to engage in long-term planning with fewer interruptions.', 'China has reached peak carbon dioxide emissions and is showing progress in energy transition, potentially setting an example for developing countries.'] 161 | --- 162 | Prompt Tokens: 427 163 | Output Tokens: 73 164 | TOTAL Tokens: 500 165 | >>>⏱️ Time to First Token: 3.67 seconds 166 | >>>⏱️ Inference time: 0:00:17.159204 167 | >>>🧮 Inference speed: 29.139 t/s 168 | >>>🏍️ Generation speed: 4.254 t/s 169 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 170 | >>>💚 User rating: All good here only speed test with speculative decoding 171 | >>>✅ NLP TAKS: Write in a list the three main key points - format output 172 | 173 | 174 | 👨‍💻 > write a "table of contents" of the provided text. Be simple and concise. 175 | [text] 176 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 177 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 178 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 179 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 180 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 181 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 182 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 183 | [end of text] 184 | 185 | "table of content": 186 | 187 | 💻 > Table of Contents 188 | 189 | 1. Introduction to China's Non-Democratic System 190 | 2. Comparison with Democratic Systems 191 | 3. Long-Term Planning as an "Advantage" 192 | 4. Environmental Achievements and Peak Emissions in 2023 193 | 5. Renewables Driving Down Carbon Emissions 194 | 6. Models for Energy Transition: China and India Leading the Way 195 | --- 196 | Prompt Tokens: 423 197 | Output Tokens: 71 198 | TOTAL Tokens: 494 199 | >>>⏱️ Time to First Token: 3.60 seconds 200 | >>>⏱️ Inference time: 0:00:19.800842 201 | >>>🧮 Inference speed: 24.948 t/s 202 | >>>🏍️ Generation speed: 3.586 t/s 203 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 204 | >>>💚 User rating: All good here only speed test with speculative decoding 205 | >>>✅ NLP TAKS: Table of Contents 206 | 207 | 208 | 👨‍💻 > Reply to the question using the provided context. If the answer is not contained in the text say "unanswerable". 209 | [context] 210 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 211 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 212 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 213 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 214 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 215 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 216 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 217 | [end of context] 218 | 219 | question: what China achieved with it's long-term planning? 220 | answer: 221 | 222 | 💻 > China achieved a significant milestone in its environmental efforts by reaching peak carbon dioxide and greenhouse gas emissions in 2023. This achievement is particularly noteworthy due to the determined increase in renewable energy installations, which has led to lower emission figures for 2024. As a result, China now offers a model for energy transition that could potentially lead developing countries to show the way forward for more developed nations like those in the West. 223 | --- 224 | Prompt Tokens: 440 225 | Output Tokens: 80 226 | TOTAL Tokens: 520 227 | >>>⏱️ Time to First Token: 3.84 seconds 228 | >>>⏱️ Inference time: 0:00:21.886925 229 | >>>🧮 Inference speed: 23.758 t/s 230 | >>>🏍️ Generation speed: 3.655 t/s 231 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 232 | >>>💚 User rating: All good here only speed test with speculative decoding 233 | >>>✅ NLP TAKS: RAG 234 | 235 | 236 | 👨‍💻 > Reply to the question only using the provided context. If the answer is not contained in the provided context say "unanswerable". 237 | 238 | question: who is Anne Frank? 239 | 240 | [context] 241 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 242 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 243 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 244 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 245 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 246 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 247 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 248 | [end of context] 249 | 250 | Remember: if you cannot answer based on the provided context, say "unanswerable" 251 | 252 | answer: 253 | 254 | 💻 > unanswerable 255 | --- 256 | Prompt Tokens: 458 257 | Output Tokens: 3 258 | TOTAL Tokens: 461 259 | >>>⏱️ Time to First Token: 3.80 seconds 260 | >>>⏱️ Inference time: 0:00:04.106847 261 | >>>🧮 Inference speed: 112.252 t/s 262 | >>>🏍️ Generation speed: 0.730 t/s 263 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 264 | >>>💚 User rating: All good here only speed test with speculative decoding 265 | >>>✅ NLP TAKS: Truthful RAG 266 | 267 | 268 | 👨‍💻 > Using the following text as a reference, write a 5-paragraphs essay about "the benefits of China economic model". 269 | 270 | [text] 271 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 272 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 273 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 274 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 275 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 276 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 277 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 278 | [end of text] 279 | Remember: use the information provided and write exactly 5 paragraphs. 280 | 281 | 💻 > The Chinese economic model, often criticized for its lack of democratic transparency and the iron-fisted rule of the Communist Party, has nonetheless demonstrated significant advantages in terms of long-term planning and sustainability. This unique governance structure allows China to focus on strategic goals without being interrupted by short-term political cycles or electoral pressures that are common in Western democracies. The ability to maintain consistent policies over extended periods can lead to more robust economic development plans and infrastructure projects, which have contributed significantly to China's rapid industrialization and urbanization. 282 | 283 | One of the most notable achievements under this model is China’s progress towards environmental sustainability. According to recent data, 2023 marked a peak in carbon dioxide emissions for China—a milestone that reflects not only its commitment but also the effectiveness of long-term planning strategies. The subsequent reduction in greenhouse gas emissions and increased investment in renewable energy sources indicate a strategic shift towards more sustainable practices. This transition is particularly noteworthy given China's status as one of the world’s largest polluters, alongside India until recently. 284 | 285 | The success of this model extends beyond environmental initiatives to include economic growth and technological advancement. By focusing on long-term goals, China has been able to invest heavily in infrastructure projects such as high-speed rail networks and smart cities, which have not only boosted domestic productivity but also enhanced its global competitiveness. These investments are part of a broader strategy that aims at reducing dependency on fossil fuels while promoting innovation across various sectors. 286 | 287 | Moreover, the Chinese economic model's emphasis on state-led development has enabled rapid industrialization and urban expansion. This approach contrasts sharply with Western democracies' more decentralized models, which can be slower to implement large-scale projects due to bureaucratic processes and political gridlock. The efficiency of China’s centralized decision-making process allows for swift implementation of policies aimed at economic growth and social welfare. 288 | 289 | In conclusion, while the Chinese model may not align with democratic ideals cherished by many Western nations, it has proven effective in achieving long-term strategic goals such as environmental sustainability and rapid industrial development. As these achievements become more evident globally, there is a growing recognition that China's approach to governance offers valuable lessons for sustainable economic growth and planning on a global scale. 290 | --- 291 | Prompt Tokens: 436 292 | Output Tokens: 451 293 | TOTAL Tokens: 887 294 | >>>⏱️ Time to First Token: 3.41 seconds 295 | >>>⏱️ Inference time: 0:01:41.724215 296 | >>>🧮 Inference speed: 8.720 t/s 297 | >>>🏍️ Generation speed: 4.434 t/s 298 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 299 | >>>💚 User rating: All good here only speed test with speculative decoding 300 | >>>✅ NLP TAKS: write content from a reference 301 | 302 | 303 | 👨‍💻 > List 5 most important topics from the following text: 304 | [text] 305 | One of the things everybody in the West knows about China is that it is not a democracy, and is instead a regime run with an iron fist by a single entity, the Chinese Communist Party, whose leadership rarely acts transparently, running the country without the need for primary elections, alternative candidacies, etc. 306 | In general, those of us who live in democracies, with relatively transparent electoral processes, tend to consider the Chinese system undesirable, little more than a dictatorship where people have no say in who governs them. 307 | That said, among the “advantages” of the Chinese system is that because the leadership never has to put its legitimacy to the vote, it can carry out very long-term planning in the knowledge that another administration isn’t going to come along and change those plans. 308 | Obviously, I put “advantages” in quotation marks because, as democrats, most of my readers would never be willing to sacrifice their freedom for greater planning, but there is no doubt that China, since its system works like this and its population seems to have accepted it for generations, intends to turn this into a comparative advantage, the term used in business when analyzing companies. 309 | It turns out that China’s capacity for long-term planning is achieving something unheard of in the West: it seems the country reached peak carbon dioxide and greenhouse gas emissions in 2023, and that the figures for 2024, driven above all by a determined increase in the installation of renewable energies, are not only lower, but apparently going to mark a turning point. 310 | China and India were until recently the planet’s biggest polluters, but they now offer a model for energy transition (there is still a long way to go; but we are talking about models, not a done deal). 311 | It could soon be the case that the so-called developing countries will be showing the West the way forward. 312 | [end of text] 313 | 314 | 💻 > Based on the provided text, here are five important topics: 315 | 316 | 1. **Chinese Political System**: The text discusses China's political system as a one-party state under the Chinese Communist Party, which does not hold primary elections or allow alternative candidacies. 317 | 318 | 2. **Long-Term Planning Capabilities**: It highlights how China’s lack of need for democratic legitimacy allows it to engage in long-term planning without fear of sudden policy changes by new administrations. 319 | 320 | 3. **Environmental Achievements**: The text notes that China has reached peak carbon dioxide and greenhouse gas emissions, with a significant reduction expected due to increased renewable energy installations. 321 | 322 | 4. **Comparison Between Chinese and Western Systems**: There is an implicit comparison between the political systems of China (a one-party state) and those in democratic nations, emphasizing differences in governance structures and their impacts on policy implementation. 323 | 324 | 5. **Energy Transition Models**: The text suggests that countries like China are setting models for energy transition, potentially leading developing nations to show a path forward for more developed Western countries. 325 | --- 326 | Prompt Tokens: 408 327 | Output Tokens: 223 328 | TOTAL Tokens: 631 329 | >>>⏱️ Time to First Token: 3.72 seconds 330 | >>>⏱️ Inference time: 0:00:49.147543 331 | >>>🧮 Inference speed: 12.839 t/s 332 | >>>🏍️ Generation speed: 4.537 t/s 333 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 334 | >>>💚 User rating: All good here only speed test with speculative decoding 335 | >>>✅ NLP TAKS: extract 5 topics 336 | 337 | 338 | 👨‍💻 > Science Fiction: The Last Transmission - Write a story that takes place entirely within a spaceship's cockpit as the sole surviving crew member attempts to send a final message back to Earth before the ship's power runs out. The story should explore themes of isolation, sacrifice, and the importance of human connection in the face of adversity. 800-1000 words. 339 | 340 | 341 | 💻 > **The Last Transmission** 342 | 343 | Captain Elara Myles sat alone in the cockpit of the Astra-1, her eyes fixed on a screen that flickered with static and occasional bursts of green text. The ship's systems were failing one by one; alarms blared intermittently as she worked feverishly to stabilize them. Her hands moved deftly over controls and switches, but it was clear the situation had spiraled beyond control. 344 | 345 | The Astra-1 had been on a routine mission to explore an uncharted asteroid belt when they encountered a massive solar flare that overloaded their shields and damaged critical systems. The ship's AI, Nova, informed her of the extent of the damage: life support would fail in less than 24 hours unless repairs could be made. 346 | 347 | Elara felt like she was drowning in data as alarms sounded one after another—engines failing, power fluctuations causing screens to flicker and dim. She knew that with each passing moment, their chances for survival dwindled further. The ship's AI had already calculated the probability of rescue: zero percent within 24 hours. 348 | 349 | Her heart ached at the thought of her crewmates trapped in cryogenic sleep pods somewhere on board—dead or alive, she couldn't tell which—and left to die alone with no hope of ever seeing Earth again. She closed her eyes and took deep breaths, trying to steady herself amidst the chaos around her. 350 | 351 | "Nova," Elara said into an empty space where a console should have been but was now just a flickering lightbulb hanging from the ceiling. "Can you confirm that we're alone?" 352 | 353 | The AI responded with its usual calm tone: "Affirmative, Captain Myles. All crew members are accounted for and in cryogenic sleep." 354 | 355 | "Understood," Elara replied, her voice steady despite the turmoil inside her chest. 356 | 357 | She turned to face a large screen displaying an Earth-like planet orbiting another star system—a simulation of what they might have seen if their mission had gone as planned. The image flickered with static but remained vivid enough for her to see familiar continents and oceans. She thought about how she would never get the chance to return home, or even lay eyes on this world again. 358 | 359 | Elara's fingers hovered over a control panel that could send out distress signals in case of emergency—signals designed specifically for reaching Earth despite interstellar distances. But sending such messages required significant power output and time; it was unlikely they'd have enough energy left by the end of their 24-hour countdown to transmit anything meaningful. 360 | 361 | "Nova," she said, her voice tinged with resignation, "how long do we have?" 362 | 363 | "A maximum of twenty-three hours and forty-five minutes until life support systems fail completely." 364 | 365 | Elara nodded grimly. She knew what had to be done next: send a final message back home before it was too late. With trembling hands, she initiated the transmission process. 366 | 367 | The screen lit up with an interface designed for sending messages across vast distances—messages that would travel at light speed and reach Earth in months or years depending on their trajectory. Elara's mind raced as she tried to think of what words could convey her deepest feelings into something concise enough for a message but meaningful nonetheless. 368 | 369 | She began typing: 370 | 371 | "Dear Earth, 372 | 373 | This is Captain Myles, Astra-1. We are currently en route back home after an unexpected encounter with a solar flare that damaged our ship's systems beyond repair. I am the sole survivor of this mission and have been tasked to send you one final message before we lose all power. 374 | 375 | I want you to know how much your planet means to me, not just as my home but also as a symbol of hope and unity among humanity. Despite losing everything else in space, I still hold onto that belief—that no matter where life takes us or what challenges come our way, together we can overcome them. 376 | 377 | To those who read this message someday: please remember the lessons learned from this mission—about resilience, sacrifice for others' sake—and let these values guide your future endeavors. May you always strive towards making Earth a better place than when I left it behind." 378 | 379 | As she typed each word carefully and deliberately, Elara felt her emotions swell within her chest like an unrelenting tide. She paused briefly to compose herself before continuing: 380 | 381 | "I am proud of what we achieved during our journey—exploring new worlds, discovering unknown phenomena—and contributing knowledge back home through scientific discoveries. But more importantly than any achievement is the bond formed between us as a crew—a testament to humanity's capacity for cooperation and mutual support even under dire circumstances. 382 | 383 | Though I may never see Earth again or meet anyone who receives this message personally, know that my spirit remains connected to you all—connected by love, hope, and shared dreams of exploration. Until we meet once more in the vast expanse of space... 384 | 385 | With deepest regards, 386 | 387 | Captain Elara Myles" 388 | 389 | Elara paused for a moment before adding her final signature: 390 | 391 | "From Astra-1." 392 | 393 | She sent the message with a heavy heart knowing that it might never reach its intended audience, but also understanding that sometimes sending something into the void is enough. The transmission completed successfully; she watched as confirmation lights blinked green on screen. 394 | 395 | With nothing left to do except wait for what was inevitable, Elara leaned back in her chair and closed her eyes. She thought about all those who had come before them—explorers brave enough to venture beyond their known worlds—and wondered if they would recognize the courage of this final transmission from a lone survivor adrift among stars. 396 | 397 | The ship's systems continued to fail around her, but Elara remained resolute in sending one last message into darkness. As she drifted off into unconsciousness amidst the hum of failing machinery and flickering screens, she whispered softly: 398 | 399 | "Goodbye... Earth." 400 | 401 | And then silence filled the cockpit as life support failed completely within minutes. 402 | 403 | The Astra-1 ceased to exist as a functioning vessel; its final transmission carried 404 | --- 405 | Prompt Tokens: 70 406 | Output Tokens: 1268 407 | TOTAL Tokens: 1338 408 | >>>⏱️ Time to First Token: 2.05 seconds 409 | >>>⏱️ Inference time: 0:04:39.288064 410 | >>>🧮 Inference speed: 4.791 t/s 411 | >>>🏍️ Generation speed: 4.540 t/s 412 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 413 | >>>💚 User rating: All good here only speed test with speculative decoding 414 | >>>✅ NLP TAKS: Creativity: 1000 words SF story 415 | 416 | 417 | 👨‍💻 > You are an AI assistant designed to provide detailed, step-by-step responses. Your outputs should follow this structure: 418 | 1. Begin with a section. 419 | 2. Inside the thinking section: 420 | a. Briefly analyze the question and outline your approach. 421 | b. Present a clear plan of steps to solve the problem. 422 | c. Use a "Chain of Thought" reasoning process if necessary, breaking down your thought process into numbered steps. 423 | 3. Include a section for each idea where you: 424 | a. Review your reasoning. 425 | b. Check for potential errors or oversights. 426 | c. Confirm or adjust your conclusion if necessary. 427 | 4. Be sure to close all reflection sections. 428 | 5. Close the thinking section with . 429 | 6. Provide your final answer in an section. 430 | Always use these tags in your responses. Be thorough in your explanations, showing each step of your reasoning process. Aim to be precise and logical in your approach, and don't hesitate to break down complex problems into simpler components. Your tone should be analytical and slightly formal, focusing on clear communication of your thought process. 431 | Remember: Both and MUST be tags and must be closed at their conclusion 432 | Make sure all are on separate lines with no other text. Do not include other text on a line containing a tag. 433 | 434 | user question: explain why it is crucial for teachers to learn how to use generative AI for their job and for the future of education. Include relevant learning path for teachers and educators. 435 | 436 | 437 | 💻 > 438 | To address the user's request, we need to analyze why it is crucial for teachers and educators to learn how to use generative AI. We will outline a clear plan of steps that highlight its importance in enhancing educational practices and preparing students for future challenges. 439 | 440 | 1. **Analyze the Importance**: Generative AI can significantly enhance teaching methods by providing personalized learning experiences, automating administrative tasks, and generating content. 441 | 2. **Outline Learning Path**: Develop a structured approach to help teachers learn about generative AI effectively. 442 | 3. **Chain of Thought**: 443 | - Understand what generative AI is and its applications in education. 444 | - Identify how it can be used to create personalized learning experiences for students. 445 | - Explore ways that generative AI can automate administrative tasks, freeing up time for more meaningful interactions with students. 446 | 4. **Reflection**: Ensure the reasoning aligns with current educational trends and future needs. 447 | 448 | 449 | 450 | ### Why It Is Crucial 451 | 452 | #### Importance of Generative AI in Education 453 | Generative AI refers to a type of artificial intelligence that generates new content based on existing data, such as text, images, or code. In education, generative AI can be used for creating personalized learning materials and assessments tailored to individual student needs. 454 | 455 | 1. **Personalized Learning**: Generative AI can analyze vast amounts of educational data to create customized lesson plans and exercises. 456 | 2. **Administrative Tasks**: Automating routine tasks like grading simple assignments or scheduling meetings allows teachers more time to focus on teaching. 457 | 3. **Content Creation**: Teachers can use generative AI tools to quickly generate new content, such as quizzes, essays prompts, or even entire lessons. 458 | 459 | #### Learning Path for Teachers and Educators 460 | 461 | 1. **Understand Generative AI Basics** 462 | - Define what generative AI is and its capabilities. 463 | - Explore different types of generative models (e.g., GPT-3). 464 | 465 | 2. **Explore Applications in Education** 466 | - Review case studies where generative AI has been used to enhance learning experiences. 467 | - Discuss how it can be integrated into existing educational systems. 468 | 469 | 3. **Practice with Tools and Platforms** 470 | - Familiarize yourself with popular generative AI tools like Anthropic, Claude, or custom models built on platforms such as Hugging Face. 471 | - Experiment by creating simple content using these tools to understand their limitations and potential. 472 | 473 | 4. **Develop Ethical Guidelines** 474 | - Learn about the ethical considerations when using generative AI in education (e.g., data privacy, bias). 475 | - Develop guidelines for responsible use of this technology. 476 | 477 | 5. **Stay Updated with Research and Trends** 478 | - Regularly read academic papers on educational applications of AI. 479 | - Engage in online forums or communities dedicated to educators adopting new technologies. 480 | 481 | ### Conclusion 482 | 483 | By learning how to effectively utilize generative AI, teachers can enhance their teaching methods, provide more personalized learning experiences for students, and manage administrative tasks more efficiently. This not only improves the quality of education but also prepares students better for a future where technology plays an increasingly significant role in various aspects of life. 484 | 485 | 486 | In conclusion, it is crucial for teachers to learn how to use generative AI because it can significantly enhance personalized learning experiences, automate routine tasks, and generate educational content. A structured learning path includes understanding the basics of generative AI, exploring its applications in education through case studies and practical exercises, developing ethical guidelines for responsible use, and staying updated with research trends. 487 | 488 | By following this approach, teachers can effectively integrate generative AI into their teaching practices to better serve students' needs and prepare them for future challenges. 489 | --- 490 | Prompt Tokens: 343 491 | Output Tokens: 808 492 | TOTAL Tokens: 1151 493 | >>>⏱️ Time to First Token: 3.19 seconds 494 | >>>⏱️ Inference time: 0:02:39.712054 495 | >>>🧮 Inference speed: 7.207 t/s 496 | >>>🏍️ Generation speed: 5.059 t/s 497 | >>>📝 Logfile: Qwen2.5-7B-Instruct_CPPSERV-SPECDECODE_1JGXF_log.txt 498 | >>>💚 User rating: All good here only speed test with speculative decoding 499 | >>>✅ NLP TAKS: Reflection prompt 500 | 501 | 502 | --------------------------------------------------------------------------------