Instructions to use danelcsb/sam2_hiera_tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danelcsb/sam2_hiera_tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="danelcsb/sam2_hiera_tiny")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("danelcsb/sam2_hiera_tiny") model = AutoModel.from_pretrained("danelcsb/sam2_hiera_tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ca0698bd98fa5da7a239e52a3ce40ce0e27ce4c99d3a81b6e98aeeae2684488
- Size of remote file:
- 156 MB
- SHA256:
- 3e92d36aaf6729dfdfa4ab80a2a679caae0182d2162fa13521bddeab09f6c701
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