Instructions to use CollectionStudio/sam2-hiera-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CollectionStudio/sam2-hiera-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="CollectionStudio/sam2-hiera-small")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("CollectionStudio/sam2-hiera-small") model = AutoModel.from_pretrained("CollectionStudio/sam2-hiera-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91da76c73cd951a1d63d8e2b1d7ec7d96313887d367f5e7cafd1b800272594f7
- Size of remote file:
- 184 MB
- SHA256:
- 95949964d4e548409021d47b22712d5f1abf2564cc0c3c765ba599a24ac7dce3
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