metadata
base_model: unsloth/Magistral-Small-2509
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: vllm
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>.
tags:
- vllm
- mistral-common
- mlx
- mlx-my-repo
mrtoots/unsloth-Magistral-Small-2509-mlx-8Bit
The Model mrtoots/unsloth-Magistral-Small-2509-mlx-8Bit was converted to MLX format from unsloth/Magistral-Small-2509 using mlx-lm version 0.26.4.
Toots' Note:
This model was converted and quantized utilizing unsloth's version of Mistral's magistral-small-2509.
Please follow and support mistral's work and support unsloth's work if you like it!
🦛 If you want a free consulting session, fill out this form to get in touch! 🤗
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mrtoots/Magistral-Small-2509-mlx-8Bit")
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)