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Update README.md (#2)
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README.md
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@@ -43,4 +43,66 @@ Here is an incomplete list of clients and libraries that are known to support GG
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## Special thanks
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🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.
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## Special thanks
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🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.
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---
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**Original README**
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# Model Card for Mathstral-7B-v0.1
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Mathstral 7B is a model specializing in mathematical and scientific tasks, based on Mistral 7B.
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You can read more in the [official blog post](https://mistral.ai/news/mathstral/).
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## Installation
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It is recommended to use `mistralai/mathstral-7B-v0.1` with [mistral-inference](https://github.com/mistralai/mistral-inference)
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```
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pip install mistral_inference>=1.2.0
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```
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## Download
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```py
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from huggingface_hub import snapshot_download
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from pathlib import Path
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mistral_models_path = Path.home().joinpath('mistral_models', 'mathstral-7B-v0.1')
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mistral_models_path.mkdir(parents=True, exist_ok=True)
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snapshot_download(repo_id="mistralai/mathstral-7B-v0.1", allow_patterns=["params.json", "consolidated.safetensors", "tokenizer.model.v3"], local_dir=mistral_models_path)
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```
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### Chat
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After installing `mistral_inference`, a `mistral-demo` CLI command should be available in your environment.
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```
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mistral-chat $HOME/mistral_models/mathstral-7B-v0.1 --instruct --max_tokens 256
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```
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You can then start chatting with the model, *e.g.* prompt it with something like:
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*"Albert likes to surf every week. Each surfing session lasts for 4 hours and costs $20 per hour. How much would Albert spend in 5 weeks?"*
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## Evaluation
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We evaluate Mathstral 7B and open-weight models of the similar size on industry-standard benchmarks.
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| Benchmarks | MATH | GSM8K (8-shot) | Odyssey Math maj@16 | GRE Math maj@16 | AMC 2023 maj@16 | AIME 2024 maj@16
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| :--- | :---: | :---: | :---: | :---: | :---: | :---: |
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| Mathstral 7B | **56.6** | 77.1 | **37.2** | 56.9 | **42.4** | **2/30** |
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| DeepSeek Math 7B | 44.4 | **80.6** | 27.6 | 44.6 | 28.0 | 0/30 |
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| Llama3 8B | 28.4 | 75.4 | 24.0 | 26.2 | 34.4 | 0/30 |
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| GLM4 9B | 50.2 | 48.8 | 18.9 | 46.2 | 36.0 | 1/30 |
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| QWen2 7B | **56.8** | 32.7 | 24.8 | **58.5** | 35.2 | **2/30** |
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| Gemma2 9B | 48.3 | 69.5 | 18.6 | 52.3 | 31.2 | 1/30 |
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## The Mistral AI Team
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Albert Jiang, Alexandre Sablayrolles, Alexis Tacnet, Alok Kothari, Antoine Roux, Arthur Mensch, Audrey Herblin-Stoop, Augustin Garreau, Austin Birky, Bam4d, Baptiste Bout, Baudouin de Monicault, Blanche Savary, Carole Rambaud, Caroline Feldman, Devendra Singh Chaplot, Diego de las Casas, Eleonore Arcelin, Emma Bou Hanna, Etienne Metzger, Gaspard Blanchet, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Harizo Rajaona, Henri Roussez, Hichem Sattouf, Ian Mack, Jean-Malo Delignon, Jessica Chudnovsky, Justus Murke, Kartik Khandelwal, Lawrence Stewart, Louis Martin, Louis Ternon, Lucile Saulnier, Lélio Renard Lavaud, Margaret Jennings, Marie Pellat, Marie Torelli, Marie-Anne Lachaux, Marjorie Janiewicz, Mickaël Seznec, Nicolas Schuhl, Niklas Muhs, Olivier de Garrigues, Patrick von Platen, Paul Jacob, Pauline Buche, Pavan Kumar Reddy, Perry Savas, Pierre Stock, Romain Sauvestre, Sagar Vaze, Sandeep Subramanian, Saurabh Garg, Sophia Yang, Szymon Antoniak, Teven Le Scao, Thibault Schueller, Thibaut Lavril, Thomas Wang, Théophile Gervet, Timothée Lacroix, Valera Nemychnikova, Wendy Shang, William El Sayed, William Marshall
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