Instructions to use saiyicao/sam2.1-hiera-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saiyicao/sam2.1-hiera-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="saiyicao/sam2.1-hiera-large")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("saiyicao/sam2.1-hiera-large") model = AutoModel.from_pretrained("saiyicao/sam2.1-hiera-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 331c3916054e327621fbbe8763fa9a538a41b041317d578973a85b963ac8441b
- Size of remote file:
- 898 MB
- SHA256:
- dc407dce21301fd94abb395c5099b4f2c455fdc8a8f261ac3d0ea6d4cd197230
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