├── .gitignore ├── Articles ├── Evaluation Metrics │ ├── Classification │ │ └── README.md │ ├── Generative Text Models │ │ └── README.md │ └── Regression │ │ └── README.md ├── Interview Preparation │ ├── Generative Models.md │ ├── Large Language Models.md │ └── README.md ├── Model Compression │ ├── DeepSpeed │ │ └── README.md │ ├── Inference Optimization │ │ └── README.md │ ├── Knowledge Distillation │ │ └── README.md │ ├── Mixed Precision Training │ │ └── README.md │ ├── Pruning │ │ └── README.md │ ├── Quantization │ │ └── README.md │ ├── README.md │ └── Sharding │ │ ├── LLM_Sharding.ipynb │ │ └── README.md ├── Models │ └── Generative Pre-trained Transformer (GPT) │ │ └── README.md ├── NLP │ ├── LLMs Overview │ │ └── README.md │ ├── NLP Embeddings │ │ ├── README.md │ │ ├── data │ │ │ └── dummy_train_skipgram.txt │ │ ├── examples │ │ │ ├── bag_of_words.py │ │ │ ├── cbow.py │ │ │ ├── compare_wor2vec_fasttext.py │ │ │ ├── elmo.py │ │ │ ├── fasttext_train.py │ │ │ ├── gensim_train.py │ │ │ ├── inference_sentence_transformer.py │ │ │ ├── positional_encoding.py │ │ │ ├── skipgram.py │ │ │ ├── tfidf.py │ │ │ ├── train_doc2vec.py │ │ │ ├── train_sentence_transformer.py │ │ │ └── use.py │ │ ├── notebooks │ │ │ ├── bag_of_words.ipynb │ │ │ ├── cbow_scratch.ipynb │ │ │ ├── compare_fasttext_word2vec.ipynb │ │ │ ├── doc2vec_inference.ipynb │ │ │ ├── elmo.ipynb │ │ │ ├── positional_encoding.ipynb │ │ │ ├── sentence_transformers.ipynb │ │ │ ├── skipgram_train_scratch.ipynb │ │ │ ├── tfidf_scratch.ipynb │ │ │ └── use.ipynb │ │ └── requirements.txt │ ├── Preprocessing │ │ └── README.md │ ├── Sampling │ │ └── README.md │ ├── Tokenization │ │ └── README.md │ └── Transformer │ │ └── Attention Is All You Need │ │ └── README.md ├── Open LLMs │ ├── Commercial Use │ │ └── README.md │ ├── Courses │ │ └── README.md │ ├── Deployment │ │ └── README.md │ ├── LLM Training Frameworks │ │ └── README.md │ ├── Neural Network Tools Visualization │ │ └── README.md │ ├── Prompting LIbraries and Tools │ │ └── README.md │ ├── Research Use │ │ └── README.md │ └── Tutorials │ │ └── README.md ├── README.md ├── Resources │ ├── Neural Network Visualization │ │ └── README.md │ └── Training and Inference Cost Analysis │ │ └── README.md └── Training │ ├── Activation Function │ └── README.md │ ├── Fine Tuning Models │ └── README.md │ ├── Flash Attention │ └── README.md │ ├── Gradient Accumulation and Checkpointing │ └── README.md │ ├── Gradient Descent and Backprop │ └── README.md │ ├── Model Summary │ └── README.md │ ├── Overfitting And Underfitting │ └── README.md │ ├── Parameter Efficient Fine-Tuning │ └── README.md │ ├── Splitting Datasets │ └── README.md │ └── Train Loss > Val Loss │ └── README.md ├── LICENSE ├── README.md ├── dataset ├── data.txt └── eval_data.txt └── example_codebase ├── Efficiently Fine Tune LLM ├── 4_bit_LLM_Quantization_with_GPTQ.ipynb ├── Dataset_creation_for_fine_tuning_LLM.ipynb ├── Efficiently_train_Large_Language_Models_with_LoRA_and_Hugging_Face.ipynb ├── FineTune_LLAMA2_with_QLORA.ipynb ├── Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.ipynb ├── Fine_tune_Llama_3_with_ORPO.ipynb ├── Fine_tuning_Microsoft_Phi_1_5b_on_custom_dataset(dialogstudio).ipynb ├── Fine_tuning_OpenAI_GPT_3_5_turbo.ipynb ├── Finetune Falcon-7b with BNB Self Supervised Training.ipynb ├── Finetune_Meta_OPT-6-1b_Model_bnb_peft.ipynb ├── Finetuning_Mistral_7b_Using_AutoTrain.ipynb ├── GPT-neo-x-20B-bnb_4bit_training.ipynb ├── Guanaco Chatbot Demo with LLaMA-7B Model.ipynb ├── Improve_ChatGPT_with_Knowledge_Graphs.ipynb ├── Introduction_to_Weight_Quantization.ipynb ├── LLM_Sharding.ipynb ├── MPT_Instruct_30B.ipynb ├── Mistral_Finetuning_SftTrainer.py ├── Mistral_finetune_trainer.py ├── Model_Family_Tree.ipynb ├── Neo4j_and_LangChain_for_Enhanced_Question_Answering.ipynb ├── PEFT Finetune-Bloom-560m-tagger.ipynb ├── RAG_LangChain.ipynb ├── RLHF_Training_for_CustomDataset_for_AnyModel.ipynb ├── Stable_Vicuna13B_8bit_in_Colab.ipynb ├── merge_model_mergekit.ipynb ├── redis_rag.ipynb └── vllm_benchmark.py ├── Inf2 LLM SM Deployment └── mistral7b_inf2.ipynb ├── config ├── __init__.py ├── deepspeed_zero3.yaml ├── enabled_bf16.json ├── enabled_fp16.json ├── global_args.py └── model_args.py ├── data_generate_prepare ├── data_generator.py └── data_prepare.py ├── decoding_strategies ├── config.py ├── decoding_inference.py └── requirements.txt ├── faster_llm_training ├── requirements.txt └── scripts │ ├── save.py │ └── tokenizer_utils.py ├── mistral_trainer_dpo ├── dpo_data_prepare │ └── dpo_data_prepare.py ├── src_dpo │ ├── dpo_data_prepare.py │ └── mistral_dpo.py ├── src_trainer │ ├── data_loader.py │ ├── data_prepare.py │ └── mistral_trainer.py └── utils │ ├── config_mistral_dpo.py │ ├── config_trainer.py │ ├── data.py │ └── models.py ├── multi_adapter_inference ├── multi_adapter_hosting_sagemaker.ipynb └── sagemaker_lorax │ ├── Dockerfile │ └── sagemaker_entrypoint.sh ├── optimize_single_model_sm_endpoint ├── mistral7b_lmi.ipynb └── utils │ ├── LineIterator.py │ └── __init__.py ├── peft_qlora_sm_training ├── mistral7b-finetune-qlora.ipynb └── scripts │ └── run_clm.py ├── t5 ├── __init__.py ├── t5_models.py └── t5_utils.py ├── text_chunk_visaulization ├── config │ └── constant.py ├── requirements.txt └── src │ ├── gradio_app.py │ ├── text_overlapper.py │ └── utils │ └── gradio_utils.py ├── train_inference ├── README.md ├── inference.py └── trainer.py ├── train_inference_accelerate ├── inference_accelerate.py ├── notebook │ └── multiple-gpu-on-notebook-using-accelerate.ipynb ├── rouge.py └── train_BART_summarization_accelerate.py ├── train_inference_peft_lora ├── README.md ├── inference_peft.py └── trainer_peft_lora.py └── vector_database ├── README.md ├── collection_service ├── embedding_generator.py └── embedding_service.py ├── data └── customer_data.csv ├── data_access ├── access_milvus.py ├── collection_base.py └── utils.py ├── requirements.txt └── scripts └── docker-compose.yaml /.gitignore: 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