Instructions to use hf-internal-testing/tiny-random-SamModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SamModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="hf-internal-testing/tiny-random-SamModel")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-SamModel") model = AutoModelForMaskGeneration.from_pretrained("hf-internal-testing/tiny-random-SamModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25e181757bf4aaac7c33fde1f16fd6fa9de61f7e0e88dbcce0e9709c5d3b6733
- Size of remote file:
- 558 kB
- SHA256:
- dbff3a2f2843814e3745bd35adf4e4801ac8b14e2159a2bc6c5f8f03facdf850
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