Instructions to use CollectionStudio/sam2.1-hiera-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CollectionStudio/sam2.1-hiera-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="CollectionStudio/sam2.1-hiera-tiny")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("CollectionStudio/sam2.1-hiera-tiny") model = AutoModel.from_pretrained("CollectionStudio/sam2.1-hiera-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba338753dfce8ea32477a60b78d5b1bfc146ac2ed7bfa291e48ed18e22b3ad71
- Size of remote file:
- 156 MB
- SHA256:
- 7402e0d864fa82708a20fbd15bc84245c2f26dff0eb43a4b5b93452deb34be69
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