language:
- en
license: apache-2.0
tags:
- pretrained
pipeline_tag: text-generation
inference:
parameters:
temperature: 0.7
Model Card for Mistral-7B-v0.1
The Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters. Mistral-7B-v0.1 outperforms Llama 2 13B on all benchmarks we tested.
For full details of this model please read our paper and release blog post.
Mistral-7B-v0.1 has the following characteristics:
- 7.3B parameters
- Byte-fallback BPE tokenizer
- Grouped-Query Attention
- 8k context window
- 4k Sliding-Window Attention
- 32000 vocab size
How to use
It is recommended to use mistralai/Mistral-7B-v0.1 with mistral_inference. For HF transformers code snippets, please keep scrolling.
Generate with mistral_inference
Install dependencies
pip install mistral_inference
Download model
from huggingface_hub import snapshot_download
from pathlib import Path
mistral_models_path = Path.home().joinpath('mistral_models', '7B-v0.1')
mistral_models_path.mkdir(parents=True, exist_ok=True)
snapshot_download(repo_id="mistralai/Mistral-7B-v0.1", allow_patterns=["params.json", "consolidated.safetensors", "tokenizer.model"], local_dir=mistral_models_path)
Demo
After installing mistral_inference, a mistral-demo CLI command should be available in your environment.
mistral-demo $HOME/mistral_models/7B-v0.1
Should give something along the following lines:
This is a test of the emergency broadcast system. This is only a test.
If this were a real emergency, you would be told what to do.
This is a test
=====================
This is another test of the new blogging software. I’m not sure if I’m going to keep it or not. I’m not sure if I’m going to keep
=====================
This is a third test, mistral AI is very good at testing. 🙂
This is a third test, mistral AI is very good at testing. 🙂
This
=====================
Generate with transformers
Install dependencies
pip install transformers
Text completion
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "mistralai/Mistral-7B-v0.1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
inputs = tokenizer("Hello my name is", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Notice
Mistral-7B is a pretrained base model and therefore does not have any moderation mechanisms.
The Mistral AI Team
Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed.