add a model card

README.md

@@ -1,3 +1,45 @@
 ---
 license: apache-2.0
+tags:
+  - merge
+  - mergekit
+  - lazymergekit
+  - macadeliccc/WestLake-7B-v2-laser-truthy-dpo
+  - FelixChao/WestSeverus-7B-DPO-v2
+  - FelixChao/Faraday-7B
+base_model:
+  - macadeliccc/WestLake-7B-v2-laser-truthy-dpo
+  - FelixChao/WestSeverus-7B-DPO-v2
+  - FelixChao/Faraday-7B
+pipeline_tag: text-generation
+model_type: mistral
+model_name: Darcy-7b
+model_creator: gmonsoon
+quantized_by: Suparious
 ---
+# 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