metadata

library_name: mlx
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>.
tags:
  - vllm
  - mistral-common
  - mlx
pipeline_tag: text-generation

JaviSwift/mistral-7b-v0.3-mixed-4-6-bit

This model JaviSwift/mistral-7b-v0.3-mixed-4-6-bit was converted to MLX format from mistralai/Mistral-7B-Instruct-v0.3 using mlx-lm version 0.26.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("JaviSwift/mistral-7b-v0.3-mixed-4-6-bit")

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)