├── AI Challenges ├── 1 min vs 10 min vs 1 hr RAG │ ├── 10min_rag.py │ ├── 1min_rag.py │ ├── AI THUMBNAIL PROMPTS.pdf │ ├── app.py │ ├── config │ │ ├── config.yml │ │ └── prompts.yml │ ├── dummy.ipynb │ ├── faiss │ │ └── 10min │ │ │ ├── index.faiss │ │ │ └── index.pkl │ └── hour_rag.py └── tree ├── AI In Cricket └── 1.Cricket_Commentary_to_Match_Report │ ├── data │ ├── match_report_gen.csv │ └── match_report_gen.parquet │ ├── future_works.txt │ ├── inference.py │ ├── inference_samples.txt │ ├── notebooks │ ├── Cricket_News_To_Cricket_Match_Report.ipynb │ └── data_prep.ipynb │ ├── sample_infer_out.png │ └── thumbnail.png ├── AI Industry Usecases └── 1_25+ AI Industry Usecases │ └── slides.pdf ├── AI Projects using LLMs ├── 1. Real Time Research Agent │ ├── README. md │ ├── app.py │ ├── config.py │ ├── requirements.txt │ ├── res │ │ ├── assistant.png │ │ └── code.png │ └── researcher.py ├── 2. Database Administrator │ ├── app.py │ ├── code.png │ ├── new_app.py │ └── thumb.png ├── 6. AI Website Scraper │ ├── requirements.txt │ ├── scraper.jpg │ ├── sourcegraph.ipynb │ └── sourcegraph.py ├── 8. LLM OS │ ├── API_Explore.ipynb │ ├── README.md │ ├── Technology.jpg │ ├── Technology.png │ ├── __init__.py │ ├── __pycache__ │ │ └── assistant.cpython-310.pyc │ ├── app.py │ ├── assistant.py │ ├── complex_nature.jpg │ ├── hello.txt │ ├── requirements.in │ ├── requirements.txt │ └── scratch │ │ ├── generate_and_plot_data.py │ │ └── open_edge_browser.py └── 9. LLM Data Analyst │ └── Data_Analyst.ipynb ├── Advanced RAG A-Z Course ├── Part1 │ ├── 01_Introduction_To_RAG.ipynb │ ├── 02_Query_Transformations.ipynb │ ├── 03_Routing_To_Datasources.ipynb │ ├── 04_Indexing_To_VectorDBs.ipynb │ └── 05_Retrieval_Mechanisms.ipynb └── tree ├── Building AI Startups with crew.AI ├── 1. AI Stock Analysis Company │ ├── stock_analysis │ │ ├── README.md │ │ ├── content.txt │ │ ├── main.py │ │ ├── poetry.lock │ │ ├── pyproject.toml │ │ ├── report.txt │ │ ├── stock_analysis_agents.py │ │ ├── stock_analysis_tasks.py │ │ └── tools │ │ │ ├── __init__.py │ │ │ ├── browser_tools.py │ │ │ ├── calculator_tools.py │ │ │ ├── search_tools.py │ │ │ └── sec_tools.py │ └── tree └── tree ├── CrewAI Course ├── markdown-validation │ ├── MarkdownTools.py │ ├── README.md │ ├── main.py │ ├── poetry.lock │ └── pyproject.toml └── ppt.pdf ├── LLMs Related ├── AI Psychiatrist │ ├── Hinglish_Chatbot_with_LoRA_Merging.ipynb │ └── tree ├── DPO on Mistral │ └── dpo_mistral.ipynb ├── Deploy LLM Chatbot │ └── todo.txt ├── Devin AI │ ├── Devin AI slides.pdf │ └── tree ├── Era of 1 Bit LLMs │ ├── 1_Bit_LLM_Pretraining.ipynb │ └── thumb.png ├── Evaluation LLMs │ ├── 2307.03109.pdf │ ├── Platypus.ipynb │ ├── Platypus.pdf │ └── content.txt ├── Finetune Any LLM For Information Extraction │ ├── Information_Extraction_Intent_Recognition.ipynb │ └── tree ├── Finetune CodeLlama │ ├── Finetune_CodeLLamA_with_inference.ipynb │ └── app.py ├── Finetune Deci │ ├── Finetune_DeciLM.ipynb │ └── thumbnail.png ├── Finetune Llama2 using QLoRA │ ├── Finetune_LLamA.ipynb │ ├── finetune_llama2.py │ └── thumbnail.png ├── Finetune Mistral │ ├── Finetune_Mistral.ipynb │ └── Readme.txt ├── Finetune Phi_1_5 │ └── Finetuning_Phi1_5.ipynb ├── Finetune XWin │ ├── Finetune_Xwin7B.ipynb │ └── thumbnail.png ├── Finetune Zephyr │ ├── Zephyr7B_Chatbot.ipynb │ ├── app.py │ └── thumbnail.png ├── GPT4o API │ ├── API_Explore.ipynb │ └── tree ├── Gemma │ ├── Finetune_Google_Gemma.ipynb │ ├── gemma-report.pdf │ └── tree ├── Generate JSON Output from LLMs for Invoices │ ├── Invoice_Processing_JsonFormer.ipynb │ └── readme.md ├── Grok Explanation │ └── grok.pdf ├── IDEFICS ImageQA │ └── IDEFICS_ImgQA.ipynb ├── LLM Crash Course │ ├── Finetune_any_LLM_crash_course.ipynb │ └── tree ├── Lightning RAG │ ├── 2312.13382.pdf │ ├── lightning_rag.ipynb │ ├── one-bit │ │ ├── index.faiss │ │ └── index.pkl │ ├── thumbnail.png │ └── usual │ │ ├── index.faiss │ │ └── index.pkl ├── Llama3 All You Need to Know │ └── Finetune_Llama3.ipynb ├── Llama3 Pretraining Till Production │ ├── Fine_tune_Llama_3_with_ORPO.ipynb │ ├── LLMS_Pretraining_to_Production.ipynb │ ├── Pretraining - FineWeb Dataset (1).png │ ├── Pretraining - FineWeb Dataset.png │ ├── app.py │ ├── requirements.txt │ ├── thumbnail.png │ └── thumbnail_new.png ├── Llama3 vs Phi3 │ ├── 2312.13382.pdf │ ├── app.py │ ├── architecture.jpeg │ ├── script.txt │ └── thumbnail (1).png ├── My Best LLM │ ├── make_best_llms_mergekit.ipynb │ └── tree ├── Phi3 │ └── Fine_tune_Phi3_with_ORPO.ipynb ├── RAG From Scratch │ ├── RAG_From_Scratch.ipynb │ └── tree ├── WhatsApp Chatbot under 15 mins │ ├── app.py │ ├── requirements.txt │ ├── tree │ └── twilio_app.py └── Zephyr Research to Production │ ├── Finetuning Code.ipynb │ ├── Paper.pdf │ ├── RAG_Invoice_Processing │ ├── data │ │ └── invoice1.pdf │ ├── information_extractor.ipynb │ ├── invoice2.pdf │ ├── res │ │ └── output.png │ └── src │ │ ├── app.py │ │ ├── config.py │ │ ├── ensemble_retriever.py │ │ └── information_extractor.py │ └── thumbnail.png ├── Langchain Projects ├── 1_Edubot │ ├── __pycache__ │ │ ├── config.cpython-38.pyc │ │ └── edubot.cpython-38.pyc │ ├── app.py │ ├── config.py │ ├── data │ │ └── llm_eval.pdf │ ├── edubot.py │ ├── faiss │ │ ├── dpo_research_paper │ │ │ ├── index.faiss │ │ │ └── index.pkl │ │ └── education │ │ │ ├── index.faiss │ │ │ └── index.pkl │ ├── res │ │ ├── build your own edubot on cpu.png │ │ ├── edubot.png │ │ ├── requirements.txt │ │ └── workflow.jpg │ └── vector_db.py ├── 2_Medbot │ ├── data │ │ └── WI_KRemedies.pdf │ ├── faiss │ │ └── medical │ │ │ ├── index.faiss │ │ │ └── index.pkl │ ├── res │ │ ├── requirements.txt │ │ ├── robot_doctor-removebg-preview.png │ │ ├── robot_doctor.jpg │ │ ├── thumbnail.png │ │ └── workflow.jpg │ ├── result.png │ └── src │ │ ├── __pycache__ │ │ └── ui.cpython-38.pyc │ │ ├── app.py │ │ └── ui.py ├── 3_YT_Buddy │ ├── __pycache__ │ │ └── llama_invocation.cpython-38.pyc │ ├── data │ │ └── transcription.txt │ ├── faiss │ │ └── video_chat │ │ │ ├── index.faiss │ │ │ └── index.pkl │ ├── requirements.txt │ ├── res │ │ ├── qa.png │ │ └── transcript.png │ └── src │ │ ├── __pycache__ │ │ ├── config.cpython-38.pyc │ │ ├── vector_db.cpython-38.pyc │ │ ├── whisper_transcribe.cpython-38.pyc │ │ └── yt_buddy.cpython-38.pyc │ │ ├── app.py │ │ ├── config.py │ │ ├── vector_db.py │ │ ├── whisper_transcribe.py │ │ └── yt_buddy.py ├── 4_Cricbot │ ├── app.py │ ├── data.ipynb │ ├── data │ │ ├── ind.csv │ │ └── t20.csv │ ├── faiss │ │ └── cricket │ │ │ ├── index.faiss │ │ │ └── index.pkl │ ├── requirements.txt │ └── res │ │ ├── cricbot.png │ │ ├── data_doc.png │ │ ├── result.png │ │ └── workflow.jpg ├── 5_AI_Researcher │ ├── app.py │ ├── config.py │ ├── misc │ │ ├── response.json │ │ └── response.txt │ ├── res │ │ ├── assistant_photo.jpg │ │ ├── output.png │ │ ├── thumbnail.png │ │ └── workflow.jpg │ └── researcher_weaviate.py ├── 6_AI_Girlfriend │ ├── app.py │ ├── config.py │ ├── gf.py │ ├── gf_audio.mp3 │ └── res │ │ ├── Screenshot 2023-09-17 105714.png │ │ ├── gf_img.jpg │ │ ├── output.png │ │ └── thumbnail.png ├── 7_AI_Financial_Advisor │ ├── data │ │ ├── savings-fitness.pdf │ │ └── sec-guide-to-savings-and-investing.pdf │ ├── res │ │ ├── after_ensemble.png │ │ ├── before_ensemble.png │ │ ├── result.png │ │ ├── thumbnail.png │ │ └── thumbnail1.png │ └── src │ │ ├── app.py │ │ ├── config.py │ │ ├── ensemble_retriever.py │ │ └── finbot.py ├── 8_AI_Evaluator │ ├── res │ │ ├── eval_result.png │ │ ├── llama-removebg-preview.png │ │ ├── llama.jpg │ │ ├── llama1-removebg-preview.png │ │ ├── llama1.jpg │ │ ├── llama2.jpg │ │ └── thumbnail.png │ └── src │ │ ├── __pycache__ │ │ ├── config.cpython-38.pyc │ │ └── eval.cpython-38.pyc │ │ ├── app.py │ │ ├── config.py │ │ └── eval.py └── 9_AI_Code_Chat │ ├── codebase │ ├── app.py │ ├── config.py │ └── researcher_weaviate.py │ ├── notebooks │ └── explore.ipynb │ ├── res │ ├── codepal.jpg │ ├── result.png │ └── thumbnail.png │ └── src │ ├── __pycache__ │ ├── codepal.cpython-38.pyc │ ├── codepal_retriever.cpython-38.pyc │ └── config.cpython-38.pyc │ ├── app.py │ ├── codepal.py │ ├── codepal_retriever.py │ └── config.py ├── Llama3 Research to Real World ├── 1_paper_explain_slide.pptx ├── 3_test_ollama_export.py ├── 4_chatbot.py ├── chatbot_backend.py ├── chatbot_frontend.py ├── notebooks │ ├── 2_2_Llama3_SFT_Inference_GGUF_Export.ipynb │ └── Llama3_Datagen.ipynb ├── ollama_exp_artifacts │ ├── Modelfile │ ├── command.txt │ └── config.json ├── tree └── utils.py ├── NLP Roadmap ├── NLP Roadmap Resources - Sheet1.csv ├── NLP Roadmap [A-Z] From Beginners to Expert.pdf ├── roadmap.png └── thumb.png ├── NLP_Projects ├── 1. Chatbot using FlanT5 LoRA │ ├── app.py │ ├── data │ │ ├── test.parquet │ │ └── train.parquet │ ├── notebooks │ │ ├── Chatbot.ipynb │ │ └── data.ipynb │ ├── requirements.txt │ └── thumbnail.png ├── 2. Text Classifier using BERT │ ├── YT_2_TextClassification.ipynb │ └── thumbnail.png ├── 3. Token Classification using BERT │ ├── BERT_NER.ipynb │ ├── Custom_BERT_NER.ipynb │ ├── app.py │ ├── ner.csv │ └── thumbnail.png ├── 4. FlanT5-AIO │ ├── FlanT5_AllInOne.ipynb │ ├── banner.png │ └── thumbnail.png └── Readme.md ├── README.md └── Research Papers ├── 1. LoRA ├── LoRA.pdf └── LoRA.pptx ├── 2. DPO ├── DPO.pdf ├── DPO_Part1_SFT.ipynb ├── DPO_Part2_DPO.ipynb ├── DPO_Part3_Inference.ipynb ├── part1_thumbnail.png └── part2_thumbnail.png ├── 3. Platypus ├── Platypus.ipynb ├── Platypus.pdf └── thumbnail.jpeg ├── 4. Mistral Architecture └── slide.pdf └── 6. 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