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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>.
pipeline_tag: text-generation
tags:
  - mlx
library_name: mlx

elimelec1/Mistral-7B-Instruct-v0.3-mlx-4bit

This model elimelec1/Mistral-7B-Instruct-v0.3-mlx-4bit 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-4bit")

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)