Instructions to use nvidia/DAM-3B-Self-Contained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Describe Anything
How to use nvidia/DAM-3B-Self-Contained with Describe Anything:
# pip install git+https://github.com/NVlabs/describe-anything from huggingface_hub import snapshot_download from dam import DescribeAnythingModel snapshot_download(nvidia/DAM-3B-Self-Contained, local_dir="checkpoints") dam = DescribeAnythingModel( model_path="checkpoints", conv_mode="v1", prompt_mode="focal_prompt", )
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba1b62d01cb427f3da20a4f70d1d4f63cd6df03393e99a7d3c0bbb52ad8af781
- Size of remote file:
- 429 MB
- SHA256:
- 7d7ef692e15d7289d747a62b21788bdc89925f7189fc583c8b02b45878b09ef1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.