---
base_model: gmonsoon/Darcy-7b
license: apache-2.0
merged_models:
- macadeliccc/WestLake-7B-v2-laser-truthy-dpo
- FelixChao/WestSeverus-7B-DPO-v2
- FelixChao/Faraday-7B
model_creator: gmonsoon
model_name: Darcy-7b
model_type: mistral
pipeline_tag: text-generation
quantized_by: Suparious
tags:
- merge
- mergekit
- lazymergekit
- macadeliccc/WestLake-7B-v2-laser-truthy-dpo
- FelixChao/WestSeverus-7B-DPO-v2
- FelixChao/Faraday-7B
---
# Darcy-7b - AWQ

- Model creator: [gmonsoon](https://huggingface.co/gmonsoon)
- Original model: [Darcy-7b](https://huggingface.co/gmonsoon/Darcy-7b)

## Model description

Darcy-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing).

- [macadeliccc/WestLake-7B-v2-laser-truthy-dpo](https://huggingface.co/macadeliccc/WestLake-7B-v2-laser-truthy-dpo)
- [FelixChao/WestSeverus-7B-DPO-v2](https://huggingface.co/FelixChao/WestSeverus-7B-DPO-v2)
- [FelixChao/Faraday-7B](https://huggingface.co/FelixChao/Faraday-7B)

### 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