Image-Text-to-Text
Safetensors
MLX
English
mlx-vlm
locateanything
vision
object-detection
grounding
nvidia
eagle
conversational
4-bit precision
Instructions to use mlx-community/LocateAnything-3B-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/LocateAnything-3B-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("mlx-community/LocateAnything-3B-4bit") config = load_config("mlx-community/LocateAnything-3B-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
- Xet hash:
- 05f8233e102946ab14405206d1db9e14a144d57dd029990a958d0b1a00c8d7ab
- Size of remote file:
- 102 MB
- SHA256:
- 56e5c216d26741be466562e90bf6f3d576f6e3c7ac64341a9101cccf94af2335
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