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
Download llm/tokenizer.model from nvidia/DAM-3B-Self-Contained: direct link, hf CLI and curl.
- Browser
- Download file 500 kB
-
https://huggingface.co/nvidia/DAM-3B-Self-Contained/resolve/refs%2Fpr%2F2/llm/tokenizer.model
- Command line
-
hf download hf://nvidia/DAM-3B-Self-Contained@refs/pr/2/llm/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/nvidia/DAM-3B-Self-Contained/resolve/refs%2Fpr%2F2/llm/tokenizer.model
500 kB
- Xet hash:
- d547ddc44a43b8b62b18f50dd23b474a69a6e182e0e9f22a0c87fdae8c910d1d
- Size of remote file:
- 500 kB
- SHA256:
- 7aedb3582ecda9fa99ee9242c17a9658f6744db083ee6ebdc8fb14857f84d220
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