Update README.md

README.md

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 ---
-license: apache-2.0
+base_model: mistralai/Mixtral-8x7B-v0.1
+inference: false
 language:
-- fr
-- it
-- de
-- es
 - en
+license: apache-2.0
+model-index:
+- name: Mixtral-8x7B
+  results: []
+model_creator: mistralai
+model_name: Mixtral-8x7B
+model_type: mixtral
+prompt_template: |
+  <|im_start|>system
+  {system_message}<|im_end|>
+  <|im_start|>user
+  {prompt}<|im_end|>
+  <|im_start|>assistant
+quantized_by: Inferless
+tags:
+- mixtral
+- vllm
+- GPTQ
 ---
-# Model Card for Mixtral-8x7B
-The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-8x7B outperforms Llama 2 70B on most benchmarks we tested.
+<!-- markdownlint-disable MD041 -->
+
+<!-- header start -->
+<!-- 200823 -->
+<div style="width: auto; margin-left: auto; margin-right: auto">
+<img src="https://pbs.twimg.com/profile_banners/1633782755669708804/1678359514/1500x500" alt="Inferless" style="width: 100%; min-width: 400px; display: block; margin: auto;">
+</div>
+<div style="display: flex; justify-content: space-between; width: 100%;">
+    <div style="display: flex; flex-direction: column; align-items: flex-start;">
+        <p style="margin-top: 0.5em; margin-bottom: 0em;">Serverless GPUs to scale your machine learning inference without any hassle of managing servers, deploy complicated and custom models with ease.</p>
+    </div>
+<!--     <div style="display: flex; flex-direction: column; align-items: flex-end;">
+        <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
+    </div> -->
+</div>
+<div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;"><a href="https://0ooatrmbp25.typeform.com/to/nzuhQtba"><b>Join Private Beta</b></a></p></div>
+<div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;">Go through <a href="https://tutorials.inferless.com/deploy-quantized-version-of-solar-10.7b-instruct-using-inferless">this tutorial</a>, for quickly deploy <b>Mixtral-8x7B-v0.1</b> using Inferless</p></div>
+<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
+<!-- header end -->
+
+# Mixtral-8x7B - GPTQ
+- Model creator: [Mistralai](https://huggingface.co/mistralai)
+- Original model: [Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1)
+
+<!-- description start -->
+## Description
+
+This repo contains GPTQ model files for [Mistralai's Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1).
+
+### About GPTQ
+
+GPTQ is a method that compresses the model size and accelerates inference by quantizing weights based on a calibration dataset, aiming to minimize mean squared error in a single post-quantization step. GPTQ achieves both memory efficiency and faster inference.
+
+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
+
+<!-- description end -->
+<!-- repositories-available start -->
+
+## Shared files, and GPTQ parameters
+
+Models are released as sharded safetensors files.
+
+| Branch | Bits | GS | AWQ Dataset | Seq Len | Size |
+| ------ | ---- | -- | ----------- | ------- | ---- |
+| [main](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1/tree/main) | 4 | 128 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 4096 | 5.96 GB
+
+<!-- README_AWQ.md-provided-files end -->
 
-For full details of this model please read our [release blog post](https://mistral.ai/news/mixtral-of-experts/).
+<!-- README_AWQ.md-text-generation-webui start -->
 
-## Warning
-This repo contains weights that are compatible with [vLLM](https://github.com/vllm-project/vllm) serving of the model as well as Hugging Face [transformers](https://github.com/huggingface/transformers) library. It is based on the original Mixtral [torrent release](magnet:?xt=urn:btih:5546272da9065eddeb6fcd7ffddeef5b75be79a7&dn=mixtral-8x7b-32kseqlen&tr=udp%3A%2F%http://2Fopentracker.i2p.rocks%3A6969%2Fannounce&tr=http%3A%2F%http://2Ftracker.openbittorrent.com%3A80%2Fannounce), but the file format and parameter names are different. Please note that model cannot (yet) be instantiated with HF.
+<!-- How to use start -->
+## How to use
+You will need the following software packages and python libraries:
+```json
+build:
+  cuda_version: "12.1.1"
+  system_packages:
+    - "libssl-dev"
+  python_packages:
+    - "torch==2.1.2"
+    - "vllm==0.2.6"
+    - "transformers==4.36.2"
+    - "accelerate==0.25.0"
+```