Instructions to use mlx-community/mistral-7b-instruct-v0.1-4bit-ngs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/mistral-7b-instruct-v0.1-4bit-ngs with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mlx-community/mistral-7b-instruct-v0.1-4bit-ngs") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use mlx-community/mistral-7b-instruct-v0.1-4bit-ngs with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "mlx-community/mistral-7b-instruct-v0.1-4bit-ngs"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mlx-community/mistral-7b-instruct-v0.1-4bit-ngs" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mlx-community/mistral-7b-instruct-v0.1-4bit-ngs", "messages": [ {"role": "user", "content": "Hello"} ] }' - Atomic Chat
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Download README.md from mlx-community/mistral-7b-instruct-v0.1-4bit-ngs: direct link, hf CLI and curl.
- Browser
- Download file 573 Bytes
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https://huggingface.co/mlx-community/mistral-7b-instruct-v0.1-4bit-ngs/resolve/main/README.md
- Command line
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hf download hf://mlx-community/mistral-7b-instruct-v0.1-4bit-ngs/README.md
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curl -L -o README.md https://huggingface.co/mlx-community/mistral-7b-instruct-v0.1-4bit-ngs/resolve/main/README.md
573 Bytes
metadata
license: apache-2.0
tags:
- finetuned
- mlx
pipeline_tag: text-generation
inference: false
mistral-7b-instruct-v0.1-4bit-ngs
This model was converted to MLX format from mistralai/mistral-7b-instruct-v0.1.
Refer to the original model card for more details on the model.
Use with mlx
pip install mlx
git clone https://github.com/ml-explore/mlx-examples.git
cd mlx-examples/llms/hf_llm
python generate.py --model mlx-community/mistral-7b-instruct-v0.1-4bit-ngs --prompt "My name is"