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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f19a9dcf3fd8dda9523a2fbf37f360d1f22e18549f7aaf499e7f0af50fd1c8b
- Size of remote file:
- 558 kB
- SHA256:
- cec0f7c491d4d1027505c59d2c71c8d6a582b6b780ba0de74665c06b0961ad6b
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