---
base_model: Sao10K/MN-12B-Lyra-v1
language:
- en
library_name: transformers
license: cc-by-nc-4.0
tags:
- 4-bit
- AWQ
- text-generation
- vllm
- aprodite
---
# Sao10K/MN-12B-Lyra-v1

- Model creator: [Sao10K](https://huggingface.co./Sao10K)
- Original model: [MN-12B-Lyra-v1](https://huggingface.co./Sao10K/MN-12B-Lyra-v1)

### About AWQ

AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, it offers faster Transformers-based inference with equivalent or better quality compared to the most commonly used GPTQ settings.

AWQ models are currently supported on Linux and Windows, with NVidia GPUs only. macOS users: please use GGUF models instead.

It is supported by:

- [Text Generation Webui](https://github.com/oobabooga/text-generation-webui) - using Loader: AutoAWQ
- [vLLM](https://github.com/vllm-project/vllm) - version 0.2.2 or later for support for all model types.
- [Hugging Face Text Generation Inference (TGI)](https://github.com/huggingface/text-generation-inference)
- [Transformers](https://huggingface.co./docs/transformers) version 4.35.0 and later, from any code or client that supports Transformers
- [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) - for use from Python code
- [Aprodite](https://github.com/PygmalionAI/aphrodite-engine) version 0.3.5 and later