Instructions to use hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-mixed_3_4 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-mixed_3_4 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-mixed_3_4") config = load_config("hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-mixed_3_4") # 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
Download tekken.json from hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-mixed_3_4: direct link, hf CLI and curl.
- Browser
- Download file 19.4 MB
-
https://huggingface.co/hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-mixed_3_4/resolve/main/tekken.json
- Command line
-
hf download hf://hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-mixed_3_4/tekken.json
-
curl -L -o tekken.json https://huggingface.co/hehua2008/Mistral-Small-3.2-24B-Instruct-2506-abliterated-MLX-mixed_3_4/resolve/main/tekken.json
19.4 MB
- Xet hash:
- 61dd9026d34bdd359b3ebe41e993d0a17a3050a8dff32b83b6c9488d76e8a27b
- Size of remote file:
- 19.4 MB
- SHA256:
- 6e2501687ccd0e1f30f36319eaf2b46958b897811e246cd8eb5d385b9e3de7d1
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