Hqq

Improvements
- Added LoRA support
- Added LoRA with fake quantization support (experimental)
- Optimizer V2 with scale update support
- Some code refactoring in quantize.py

No improvements over v0.1.1. Just removed Pytorch from the dependencies and updated the Readme.

Improvements:
- Added Mixtral support for Hugging Face.
- Added support for layer-wise custom quantization configs.

Improvements
- Added compile backend support
- Added Aten C++ backend (experimental)
- Faster bit unpacking via pre-allocated empty tensor
- Added VLLM support
- Refactoring to call `quantize_model()` on instances

Supported models
- Llama (Hugging Face + VLLM)
- ViT-CLIP (timm)

Limitations
- HF only supports single GPU runtime.
- VLLM only supports single GPU with a single worker.
- The compile backend sometimes creates issues with async runtime
- Doesn't support PEFT (LoRA, etc.).

Alpha version with basic Hugging Face/Timm support.

Supported models:

- Llama (Hugging Face)
- ViT (timm)

Limitations:
- Uses a pure Pytorch implementation without optimizations.
- Only supports single GPU runtime.
- Doesn't support Peft (LoRA, etc.) for custom training.