L

llm-training

🔧🔗https://github.com/pytorch/torchtune PyTorch native post-training library

🕸️🔗pytorch.org/torchtune/main/

https://github.com/InternLM/xtuner An efficient, flexible and full-featured toolkit for fine-tuning LLM (InternLM2, Llama3, Phi3, Qwen, Mistral, ...)

LLM training in simple, raw C/CUDA LLMs in simple, pure C/CUDA with no need for 245MB of PyTorch or 107MB of cPython. Current focus is on pretraining, in particular reproducing the GPT-2 and GPT-3 miniseries, along with a parallel PyTorch ref

https://github.com/coqui-ai/snakepit 🐍 Coqui's machine learning job scheduler

https://github.com/lm-sys/llm-decontaminator Code for the paper "Rethinking Benchmark and Contamination for Language Models with Rephrased Samples"