Instructions to use giladvdn/test-sam-handler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use giladvdn/test-sam-handler with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="giladvdn/test-sam-handler")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("giladvdn/test-sam-handler") model = AutoModelForMaskGeneration.from_pretrained("giladvdn/test-sam-handler") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e9c7753a722d17c2c83b6e7903ee52c240aa014a283bc2a3751f8f8050207f30
- Size of remote file:
- 2.56 GB
- SHA256:
- 9a14fd58481d203300024d94128edfce246b4b0db7e0b548ed52bf63578cbc38
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