Instructions to use 1038lab/sam3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 1038lab/sam3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="1038lab/sam3")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("1038lab/sam3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c183349ef14079c62129d1637bd1d85741f1d944dfa3afe96d9449bb4d81661
- Size of remote file:
- 1.75 GB
- SHA256:
- 9ba99c92703c2e8b4f47de2d34a539bb8e18923049e238b780d70dbe6368eb03
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