Mathstral 7B v0.1 EU AI Act Compliance Profile

Model Card for Mathstral-7b-v0.1

Mathstral 7B is a model specializing in mathematical and scientific tasks, based on Mistral 7B. You can read more in the official blog post.

Installation

It is recommended to use mistralai/Mathstral-7b-v0.1 with mistral-inference

Download

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)

Chat

After installing mistral_inference, a mistral-demo CLI command should be available in your environment.

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?"

Usage in transformers

To use this model within the transformers library, install the latest release with pip install --upgrade transformers and run, for instance:

from transformers import pipeline
import torch

checkpoint = "mistralai/Mathstral-7b-v0.1"
pipe = pipeline("text-generation", checkpoint, device_map="auto", torch_dtype=torch.bfloat16)

prompt = [{"role": "user", "content": "What are the roots of unity?"}]
out = pipe(prompt, max_new_tokens = 512)

print(out[0]['generated_text'][-1])
>>> "{'role': 'assistant', 'content': ' The roots of unity are the complex numbers that satisfy the equation $z^n = 1$, where $n$ is a positive integer. These roots are evenly spaced around the unit circle in the complex plane, and they

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Tags

Library