Convert llama.cpp to Pytorch

The llama.cpp library is a cornerstone in language modeling with a variety of quantization techniques, but it's largely used within its own ecosystem. This repo's aim is to make these methods more accessible to the PyTorch community.

This repo provides an example for converting GGUF files back into PyTorch state dict, allowing you to run inference purely in PyTorch. Currently supported models:

• LLaMA / Mistral
• Mixtral
• Qwen / Qwen2
• InternLM2
• StarCoder2
• Orion
• MiniCPM
• Xverse
• Command-r-v01
• StableLM
• Gemma

The code is largely inspired by the original llama.cpp and GPT-Fast.

Getting Started

• Install the CUDA extension

python setup.py install

• Convert GGUF file to torch state dict

python convert.py --input tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf --output TinyLlama-Q4_K_M

• Running inference

python generate.py --checkpoint_path TinyLlama-Q4_K_M --interactive --compile

torch.compile will take minutes, you can also run in eager mode without --compile flag.

Todo

• Add support to more model
• Support partitioned model
• Support new MoE breaking change