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:
- 92f89af06c24b76fd95b6ea3fa20186d751ca6826a486e9afa07d2368e6d6ab8
- Size of remote file:
- 381 kB
- SHA256:
- a52b411324d2bfe234a1e3774180754221eebbc377b03c140964f148938f96ec
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