Fine-tuning open-source large and small instruct/chat language models (LLMs & SLMs) from the Hugging Face Model Hub using public datasets.
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Updated
Aug 31, 2024 - Jupyter Notebook
Fine-tuning open-source large and small instruct/chat language models (LLMs & SLMs) from the Hugging Face Model Hub using public datasets.
A comprehensive example of fine-tuning Mistral 7B models with Langchain and LlamaCPP, using Jupyter notebooks for experimentation.
A curated collection of notebooks exploring Large Language Models and Machine Learning — including prompt engineering, model evaluation, and hands-on experiments.
Google Colab notebooks for deploying, quantizing (4-bit BitsAndBytes), serving (Flask/ngrok & Ollama), and inferencing LLMs (DeepSeek-R1, Mistral-7B, Qwen2.5-Coder).
23 hands-on Colab notebooks for LLM fine-tuning (LoRA, QLoRA, PEFT, RLHF), RAG pipelines, knowledge graphs, 1-bit quantization & MLflow evaluation — Llama 2, Mistral 7B, Falcon, Gemma 2, Phi-1.5, GPT-3.5 & more.
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