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Update README.md
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patrickvonplaten committed May 29, 2024
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| Name | Download | md5sum |
|-------------|-------|-------|
| 7B Instruct v3 | https://models.mistralcdn.com/mistral-7b-v0-3/mistral-7B-Instruct-v0.3.tar | `80b71fcb6416085bcb4efad86dfb4d52` |
| 7B Instruct | https://models.mistralcdn.com/mistral-7b-v0-3/mistral-7B-Instruct-v0.3.tar | `80b71fcb6416085bcb4efad86dfb4d52` |
| 8x7B Instruct | https://models.mistralcdn.com/mixtral-8x7b-v0-1/Mixtral-8x7B-v0.1-Instruct.tar (**Updated model coming soon!**) | `8e2d3930145dc43d3084396f49d38a3f` |
| 8x22 Instruct | https://models.mistralcdn.com/mixtral-8x22b-v0-3/mixtral-8x22B-Instruct-v0.3.tar | `471a02a6902706a2f1e44a693813855b` |
| 7B Base | https://models.mistralcdn.com/mistral-7b-v0-3/mistral-7B-v0.3.tar | `0663b293810d7571dad25dae2f2a5806` |
| 8x7B | **Updated model coming soon!** | - |
| 8x22B | https://models.mistralcdn.com/mixtral-8x22b-v0-3/mixtral-8x22B-v0.3.tar | `a2fa75117174f87d1197e3a4eb50371a` |
| Codestral 22B | https://models.mistralcdn.com/codestral-22b-v0-1/codestral-22B-v0.1.tar | TODO |

Note:
- **Important**:
- `mixtral-8x22B-Instruct-v0.3.tar` is exactly the same as [Mixtral-8x22B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1), only stored in `.safetensors` format
- `mixtral-8x22B-v0.3.tar` is the same as [Mixtral-8x22B-v0.1](https://huggingface.co/mistralai/Mixtral-8x22B-v0.1), but has an extended vocabulary of 32768 tokens.
- `codestral-22B-v0.1.tar` has a custom non-commercial license, called [
- All of the listed models above supports function calling. For example, Mistral 7B Base/Instruct v3 is a minor update to Mistral 7B Base/Instruct v2, with the addition of function calling capabilities.
- The "coming soon" models will include function calling as well.
- You can download the previous versions of our models from our [docs](https://docs.mistral.ai/getting-started/open_weight_models/#downloading).
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## Usage

The following sections give an overview of how to run the model from the Command-line interface or from Python.
The following sections give an overview of how to run the model from the Command-line interface (CLI) or directly within Python.

### CLI

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