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Go through this tutorial, for quickly deploy Mixtral-8x7B-v0.1 using Inferless
Mixtral-8x7B - GPTQ
- Model creator: Mistralai
- Original model: Mixtral-8x7B-v0.1
Description
This repo contains GPTQ model files for Mistralai's 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 - using Loader: AutoAWQ
- vLLM - version 0.2.2 or later for support for all model types.
- Hugging Face Text Generation Inference (TGI)
- Transformers version 4.35.0 and later, from any code or client that supports Transformers
- AutoAWQ - for use from Python code
Shared files, and GPTQ parameters
Models are released as sharded safetensors files.
Branch | Bits | GS | AWQ Dataset | Seq Len | Size |
---|---|---|---|---|---|
main | 4 | 128 | VMware Open Instruct | 4096 | 5.96 GB |
How to use
You will need the following software packages and python libraries:
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"
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Base model
mistralai/Mixtral-8x7B-v0.1