metadata

language:
  - en
  - fr
  - de
  - es
  - pt
  - it
  - ja
  - ko
  - ru
  - zh
  - ar
  - fa
  - id
  - ms
  - ne
  - pl
  - ro
  - sr
  - sv
  - tr
  - uk
  - vi
  - hi
  - bn
license: apache-2.0
library_name: mlx
inference: false
base_model: mlx-community/Magistral-Small-2506-bf16
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
  - mlx
  - mlx-my-repo

janboe91/Magistral-Small-2506-bf16-mlx-6Bit

The Model janboe91/Magistral-Small-2506-bf16-mlx-6Bit was converted to MLX format from mlx-community/Magistral-Small-2506-bf16 using mlx-lm version 0.22.3.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("janboe91/Magistral-Small-2506-bf16-mlx-6Bit")

prompt="hello"

if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, tokenize=False, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)