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
File size: 436 Bytes
38fc899 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"add_prefix_space": null,
"backend": "tokenizers",
"bos_token": "<s>",
"clean_up_tokenization_spaces": false,
"eos_token": "</s>",
"is_local": true,
"legacy": true,
"local_files_only": false,
"model_max_length": 1000000000000000019884624838656,
"pad_token": "<pad>",
"processor_class": "Mistral3Processor",
"tokenizer_class": "TokenizersBackend",
"unk_token": "<unk>",
"use_default_system_prompt": false
}
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