Instructions to use hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-4bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-4bit") config = load_config("hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-4bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-4bit: direct link, hf CLI and curl.
- Browser
- Download file 413 Bytes
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https://huggingface.co/hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-4bit/resolve/main/README.md
- Command line
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hf download hf://hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-4bit/README.md
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curl -L -o README.md https://huggingface.co/hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-4bit/resolve/main/README.md
413 Bytes
metadata
language: en
pipeline_tag: image-text-to-text
library_name: mlx
tags:
- mlx
hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-4bit
Use with mlx
pip install -U mlx-vlm
python -m mlx_vlm.generate --model hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-4bit --max-tokens 100 --temperature 0.0 --prompt "Describe this image." --image <path_to_image>