metadata
base_model: mistralai/Magistral-Small-2507
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
library_name: mlx
license: apache-2.0
inference: false
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:
- vllm
- mistral-common
- transformers
- mlx
Magistral-Small-2507-320k-q6-mlx
This is an experimental quant extended to 320k context.
This model Magistral-Small-2507-320k-q6-mlx was converted to MLX format from mistralai/Magistral-Small-2507 using mlx-lm version 0.26.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Magistral-Small-2507-320k-q6-mlx")
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)