Text Generation
Transformers
PyTorch
Safetensors
mistral
finetuned
mistral-common
conversational
Eval Results
text-generation-inference
Instructions to use mistralai/Mistral-7B-Instruct-v0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mistralai/Mistral-7B-Instruct-v0.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.2") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use mistralai/Mistral-7B-Instruct-v0.2 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-Instruct-v0.2" --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/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mistralai/Mistral-7B-Instruct-v0.2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/mistralai/Mistral-7B-Instruct-v0.2
- SGLang
How to use mistralai/Mistral-7B-Instruct-v0.2 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-Instruct-v0.2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mistralai/Mistral-7B-Instruct-v0.2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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-Instruct-v0.2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mistralai/Mistral-7B-Instruct-v0.2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use mistralai/Mistral-7B-Instruct-v0.2 with Docker Model Runner:
docker model run hf.co/mistralai/Mistral-7B-Instruct-v0.2
READ ME:
#169
by TriboSymbolicAI - opened
We operate a private symbolic-AI research unit across Germany, UAE, and Iraq for petroleum and lubricant market forecasting. We require local deployment of Mistral-7B-Instruct for modeling geopolitical and commercial pulse analysis using llama.cpp. The model will remain strictly private for internal forecasting. Supporting technical documentation and research available upon request.
TriboSymbolicAI changed pull request title from Update README.md to Vaultlube-Tribo-Golden-Naft Group
TriboSymbolicAI changed pull request status to closed
TriboSymbolicAI changed pull request title from Vaultlube-Tribo-Golden-Naft Group to READ ME: Vaultlube-Tribo-Golden-Naft Group
TriboSymbolicAI changed pull request status to open
TriboSymbolicAI changed pull request status to closed
TriboSymbolicAI changed pull request status to open
TriboSymbolicAI changed pull request title from READ ME: Vaultlube-Tribo-Golden-Naft Group to READ ME: