by MaziyarPanahi
Open source · 83k downloads · 7 likes
Mathstral 7B v0.1 GGUF is an artificial intelligence model specialized in mathematical and scientific tasks, optimized to solve complex problems with precision. It is built on the Mistral 7B architecture and excels in logical reasoning, advanced calculations, and structured data analysis. Designed for educational, professional, or research applications, it addresses questions requiring detailed problem-solving steps or conceptual explanations. Its GGUF version, which is lighter and compatible with many local tools, makes it accessible without relying on the cloud while maintaining high performance. This model stands out for its ability to handle technical problems while remaining adaptable to a variety of contexts.
MaziyarPanahi/mathstral-7B-v0.1-GGUF contains GGUF format model files for mistralai/mathstral-7B-v0.1.
GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.
Here is an incomplete list of clients and libraries that are known to support GGUF:
🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible.
Original README
Mathstral 7B is a model specializing in mathematical and scientific tasks, based on Mistral 7B. You can read more in the official blog post.
It is recommended to use mistralai/mathstral-7B-v0.1 with mistral-inference
pip install mistral_inference>=1.2.0
from huggingface_hub import snapshot_download
from pathlib import Path
mistral_models_path = Path.home().joinpath('mistral_models', 'mathstral-7B-v0.1')
mistral_models_path.mkdir(parents=True, exist_ok=True)
snapshot_download(repo_id="mistralai/mathstral-7B-v0.1", allow_patterns=["params.json", "consolidated.safetensors", "tokenizer.model.v3"], local_dir=mistral_models_path)
After installing mistral_inference, a mistral-demo CLI command should be available in your environment.
mistral-chat $HOME/mistral_models/mathstral-7B-v0.1 --instruct --max_tokens 256
You can then start chatting with the model, e.g. prompt it with something like:
"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?"
We evaluate Mathstral 7B and open-weight models of the similar size on industry-standard benchmarks.
| Benchmarks | MATH | GSM8K (8-shot) | Odyssey Math maj@16 | GRE Math maj@16 | AMC 2023 maj@16 | AIME 2024 maj@16 |
|---|---|---|---|---|---|---|
| Mathstral 7B | 56.6 | 77.1 | 37.2 | 56.9 | 42.4 | 2/30 |
| DeepSeek Math 7B | 44.4 | 80.6 | 27.6 | 44.6 | 28.0 | 0/30 |
| Llama3 8B | 28.4 | 75.4 | 24.0 | 26.2 | 34.4 | 0/30 |
| GLM4 9B | 50.2 | 48.8 | 18.9 | 46.2 | 36.0 | 1/30 |
| QWen2 7B | 56.8 | 32.7 | 24.8 | 58.5 | 35.2 | 2/30 |
| Gemma2 9B | 48.3 | 69.5 | 18.6 | 52.3 | 31.2 | 1/30 |
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