A simple, performant, and scalable Jax LLM!
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Go ahead and axolotl questions
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
llama.cpp fork with additional SOTA quants and improved performance
A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
🏗️ Fine-tune, build, and deploy open-source LLMs easily!
MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model.
