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
- LM Studio
- Xet hash:
- 735cba2020dfd79de6ad2c99ac8326b067d85f4a09ccfa4522041d6ba346e1cf
- Size of remote file:
- 25 MB
- SHA256:
- 3f4083674bacb26f43d1f68f5529dac7ed4c713dca724d90b718358253453aba
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