Instructions to use CollectionStudio/sam2-hiera-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CollectionStudio/sam2-hiera-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="CollectionStudio/sam2-hiera-tiny")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("CollectionStudio/sam2-hiera-tiny") model = AutoModel.from_pretrained("CollectionStudio/sam2-hiera-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cccdbf88e48ab0a87fc4bbbc0ab619f0c97a572d370280f30e86f991bd388a9
- Size of remote file:
- 156 MB
- SHA256:
- 1449035ba6ba2ed524c646da989e5cb3a9b93b97f1c1b2d474e598c3b748d99f
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