metadata

language:
  - en
license: apache-2.0
library_name: transformers
tags:
  - mistral
  - mixtral
  - moe
model_name: Mixtral 8X7B - bnb 4-bit
inference: false
model_type: mixtral
pipeline_tag: text-generation
quantized_by: ybelkada

Mixtral 8x7B Instruct-v0.1 - `bitsandbytes` 4-bit

This repository contains the bitsandbytes 4-bit quantized version of mistralai/Mixtral-8x7B-Instruct-v0.1. To use it, make sure to have the latest version of bitsandbytes and transformers installed from source:

Loading this model as such: will directly load the quantized model in 4-bit precision.

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "ybelkada/Mixtral-8x7B-Instruct-v0.1-bnb-4bit"
model = AutoModelForCausalLM.from_pretrained(model_id)

Note you need a CUDA-compatible GPU device to run low-bit precision models with bitsandbytes

Mixtral 8x7B Instruct-v0.1 - bitsandbytes 4-bit

Mixtral 8x7B Instruct-v0.1 - `bitsandbytes` 4-bit