Concepts and examples on using and training LLMs
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Updated
May 27, 2024 - Jupyter Notebook
Concepts and examples on using and training LLMs
Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs ,META LLAMA3 , Agents.
This repository contains code for fine-tuning the LLama3 8b model using Alpaca prompts to generate Java codes. The code is based on a Google Colab notebook.
Repository for running LLMs efficiently on Mac silicon (M1, M2, M3). Features Jupyter notebook for Meta-Llama-3 setup using MLX framework, with install guide & perf tips. Aims to optimize LLM performance on Mac silicon for devs & researchers.
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