Instructions to use mlx-community/Mistral-7B-Instruct-v0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Mistral-7B-Instruct-v0.2 with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mlx-community/Mistral-7B-Instruct-v0.2") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- MLX LM
How to use mlx-community/Mistral-7B-Instruct-v0.2 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "mlx-community/Mistral-7B-Instruct-v0.2" --prompt "Once upon a time"
no gpu utilization
#10 opened over 2 years ago
by
Phanindra49
Convert weights.npz to safetensors
#9 opened over 2 years ago
by
projectprogramamark
Long latency and low gpu utilization
#8 opened over 2 years ago
by
Scott0612
Quantised model for mlx-community/Mistral-7B-Instruct-v0.2
1
#6 opened over 2 years ago
by
akashicmarga
Script that converted this model?
👍 1
#5 opened over 2 years ago
by
nheagy