Image-Text-to-Text
MLX
Safetensors
English
locateanything
nvidia
eagle
vision
object-detection
grounding
conversational
custom_code
Instructions to use eadx/LocateAnything-3B-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use eadx/LocateAnything-3B-MLX 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("eadx/LocateAnything-3B-MLX") config = load_config("eadx/LocateAnything-3B-MLX") # 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 generation_config.json from eadx/LocateAnything-3B-MLX: direct link, hf CLI and curl.
- Browser
- Download file 121 Bytes
-
https://huggingface.co/eadx/LocateAnything-3B-MLX/resolve/main/generation_config.json
- Command line
-
hf download hf://eadx/LocateAnything-3B-MLX/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/eadx/LocateAnything-3B-MLX/resolve/main/generation_config.json
121 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 151643, | |
| "eos_token_id": 151645, | |
| "transformers_version": "4.51.0" | |
| } | |