Image-Text-to-Text
MLX
Safetensors
mage_vl
vision-language-model
video-understanding
mage-vl
conversational
custom_code
8-bit precision
Instructions to use mlx-community/Mage-VL-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Mage-VL-8bit 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/Mage-VL-8bit") config = load_config("mlx-community/Mage-VL-8bit") # 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 model.safetensors from mlx-community/Mage-VL-8bit: direct link, hf CLI and curl.
- Browser
- Download file 5.35 GB
-
https://huggingface.co/mlx-community/Mage-VL-8bit/resolve/main/model.safetensors
- Command line
-
hf download hf://mlx-community/Mage-VL-8bit/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/mlx-community/Mage-VL-8bit/resolve/main/model.safetensors
5.35 GB
- Xet hash:
- 74f37b8cd8c2be72a9896b39aee693f6d9d77a34fcda80cd8a610536743763d3
- Size of remote file:
- 5.35 GB
- SHA256:
- 2442f282dafd316571c1603a4695baea86b1433a5fea7202b2e3784f06b44f45
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