Image-Text-to-Text
MLX
Safetensors
English
idefics3
mlx-vlm
quantized
8-bit precision
conversational
Instructions to use mlx-community/CodeFormulaV2-mlx-q8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/CodeFormulaV2-mlx-q8 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("mlx-community/CodeFormulaV2-mlx-q8") config = load_config("mlx-community/CodeFormulaV2-mlx-q8") # 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
- LM Studio
- Xet hash:
- 8e7941d8ea39054ad93355db3d56c7efd5c07dad8faba9b1cc9608884872553d
- Size of remote file:
- 416 MB
- SHA256:
- 4a2af66400728d0c7cc278fe100ae06a5050f4693f2d95a3e4f03856277f79b7
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