metadata
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.3
extra_gated_description: >-
If you want to learn more about how we process your personal data, please read
our <a href="https://mistral.ai/terms/">Privacy Policy</a>.
library_name: mlx
tags:
- mlx
pipeline_tag: text-generation
elimelec1/Mistral-7B-Instruct-v0.3-mlx-3bit
This model elimelec1/Mistral-7B-Instruct-v0.3-mlx-3bit was converted to MLX format from mistralai/Mistral-7B-Instruct-v0.3 using mlx-lm version 0.26.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("elimelec1/Mistral-7B-Instruct-v0.3-mlx-3bit")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)