Instructions to use mistralai/Mistral-7B-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mistralai/Mistral-7B-v0.1 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="mistralai/Mistral-7B-v0.1")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", device_map="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use mistralai/Mistral-7B-v0.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Install mistral-common:
pip install --upgrade mistral-common
# Start the vLLM server:
vllm serve "mistralai/Mistral-7B-v0.1" --tokenizer_mode mistral --config_format mistral --load_format mistral --tool-call-parser mistral --enable-auto-tool-choice
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mistralai/Mistral-7B-v0.1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/mistralai/Mistral-7B-v0.1

SGLang

How to use mistralai/Mistral-7B-v0.1 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "mistralai/Mistral-7B-v0.1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mistralai/Mistral-7B-v0.1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "mistralai/Mistral-7B-v0.1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mistralai/Mistral-7B-v0.1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use mistralai/Mistral-7B-v0.1 with Docker Model Runner:
```
docker model run hf.co/mistralai/Mistral-7B-v0.1
```

Disable normalization for special tokens

#26

by lewtun HF Staff - opened Oct 2, 2023

base: refs/heads/main

←

from: refs/pr/26

Discussion Files changed

-3

lewtun

Oct 2, 2023

•

edited Oct 3, 2023

This PR fixes an issue in the Mistral tokenizer where the special tokens aren't tokenized correctly if concatenated with other characters, e.g.

from transformers import AutoTokenizer 

tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")

# Gives correct IDs: {'input_ids': [2], 'attention_mask': [1]}
tokenizer("</s>", add_special_tokens=False) 

# Gives correct IDs: {'input_ids': [842], 'attention_mask': [1]}
tokenizer(".", add_special_tokens=False)

# Gives incorrect IDs: {'input_ids': [842, 700, 28713, 28767], 'attention_mask': [1, 1, 1, 1]}
tokenizer(".</s>", add_special_tokens=False)

The solution is to disable normalization for all the special tokens, which is what this PR does. Note that until this PR is merged, the following workaround with the slow tokenizer can be adopted:

from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1", from_slow = True)

Disable normalization for special tokens5f9cf2a1

lerela changed pull request status to merged Oct 3, 2023

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment