---
language:
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license: other
license_name: mrl
inference: false
license_link: https://mistral.ai/licenses/MRL-0.1.md
extra_gated_prompt: >-
# Mistral AI Research License
If You want to use a Mistral Model, a Derivative or an Output for any purpose that is not expressly authorized under this Agreement, You must request a license from Mistral AI, which Mistral AI may grant to You in Mistral AI's sole discretion. To discuss such a license, please contact Mistral AI via the website contact form: https://mistral.ai/contact/
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## 2. License
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You include in any such Derivatives made by or for You prominent notices stating that You modified the concerned Mistral Model; and
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## 7. Termination
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## 8. General provisions
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## 9. Definitions
"Agreement": means this Mistral AI Research License agreement governing the access, use, and Distribution of the Mistral Models, Derivatives and Outputs.
"Derivative": means any (i) modified version of the Mistral Model (including but not limited to any customized or fine-tuned version thereof), (ii) work based on the Mistral Model, or (iii) any other derivative work thereof.
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"You": means the individual or entity entering into this Agreement with Mistral AI.
*Mistral AI processes your personal data below to provide the model and enforce its license. If you are affiliated with a commercial entity, we may also send you communications about our models. For more information on your rights and data handling, please see our privacy policy.*
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library_name: vllm
quantized_by: bartowski
pipeline_tag: text-generation
base_model: mistralai/Mistral-Large-Instruct-2411
base_model_relation: quantized
---
## Exllama v2 Quantizations of Mistral-Large-Instruct-2411
Using turboderp's ExLlamaV2 v0.2.4 for quantization.
The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)
Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
Conversion was done using the default 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-Large-Instruct-2411
6.5 bits per weight
5.0 bits per weight
4.25 bits per weight
3.75 bits per weight
3.5 bits per weight
3.0 bits per weight
2.2 bits per weight
## Download instructions
With git:
```shell
git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Mistral-Large-Instruct-2411-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-Large-Instruct-2411-exl2`:
```shell
mkdir Mistral-Large-Instruct-2411-exl2
huggingface-cli download bartowski/Mistral-Large-Instruct-2411-exl2 --local-dir Mistral-Large-Instruct-2411-exl2
```
To download from a different branch, add the `--revision` parameter:
Linux:
```shell
mkdir Mistral-Large-Instruct-2411-exl2-6_5
huggingface-cli download bartowski/Mistral-Large-Instruct-2411-exl2 --revision 6_5 --local-dir Mistral-Large-Instruct-2411-exl2-6_5
```
Windows (which apparently doesn't like _ in folders sometimes?):
```shell
mkdir Mistral-Large-Instruct-2411-exl2-6.5
huggingface-cli download bartowski/Mistral-Large-Instruct-2411-exl2 --revision 6_5 --local-dir Mistral-Large-Instruct-2411-exl2-6.5
```