Instructions to use facebook/sam-vit-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/sam-vit-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="facebook/sam-vit-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("facebook/sam-vit-base") model = AutoModelForMaskGeneration.from_pretrained("facebook/sam-vit-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.bdccba0
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Update README.md (#2)
- Update README.md (0b40a4fdabc45afbaa0b6278d743eeb621d2f9ba) - Update README.md (f6d135382339e4c0dfde18a7c079a536dc2e1e92) Co-authored-by: Younes Belkada <ybelkada@users.noreply.huggingface.co>b5fc599
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Add TF weights
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Update README.md (#1)
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Update README.md
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initial commit
Younes Belkada3d25a77