Instructions to use CollectionStudio/sam2.1-hiera-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CollectionStudio/sam2.1-hiera-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="CollectionStudio/sam2.1-hiera-small")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("CollectionStudio/sam2.1-hiera-small") model = AutoModel.from_pretrained("CollectionStudio/sam2.1-hiera-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94accd8994c9022fc172117f01e7d821b8314833af42ce483de03813c6b865e5
- Size of remote file:
- 184 MB
- SHA256:
- 6d1aa6f30de5c92224f8172114de081d104bbd23dd9dc5c58996f0cad5dc4d38
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