Access large language models from the command-line
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llama.cpp fork with additional SOTA quants and improved performance
Benchmarking large language models' complex reasoning ability with chain-of-thought prompting
LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis.
Build LLM-powered applications in Ruby
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Harness LLMs with Multi-Agent Programming
