---
license: apache-2.0
pipeline_tag: text-generation
tags:
- finetuned
inference:
parameters:
temperature: 0.7
quantized_by: bartowski
---
## Exllama v2 Quantizations of Mistral-7B-Instruct-v0.2
Using turboderp's ExLlamaV2 v0.0.10 for quantization.
Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
Conversion was done using VMWareOpenInstruct.parquet as calibration dataset.
Default arguments used except when the bits per weight is above 6.0, at that point the lm_head layer is quantized at 8 bits per weight instead of the default 6.
Original model: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2
3.75 bits per weight
4.0 bits per weight
5.0 bits per weight
6.0 bits per weight
7.0 bits per weight
8.0 bits per weight
## Download instructions
With git:
```shell
git clone --single-branch --branch 4_0 https://huggingface.co/bartowski/Mistral-7B-Instruct-v0.2-exl2
```
With huggingface hub (credit to TheBloke for instructions):
```shell
pip3 install huggingface-hub
```
To download the `main` (only useful if you only care about measurement.json) branch to a folder called `Mistral-7B-Instruct-v0.2-exl2`:
```shell
mkdir Mistral-7B-Instruct-v0.2-exl2
huggingface-cli download bartowski/Mistral-7B-Instruct-v0.2-exl2 --local-dir Mistral-7B-Instruct-v0.2-exl2 --local-dir-use-symlinks False
```
To download from a different branch, add the `--revision` parameter:
```shell
mkdir Mistral-7B-Instruct-v0.2-exl2
huggingface-cli download bartowski/Mistral-7B-Instruct-v0.2-exl2 --revision 4_0 --local-dir Mistral-7B-Instruct-v0.2-exl2 --local-dir-use-symlinks False
```