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:
- c92073cfd2676a857ff1301c71ece4e1826f184c5c46bd6aa4e8700d8c1bd6e1
- Size of remote file:
- 418 kB
- SHA256:
- dc91614645e3c67594236f87731e8461d2143ae484784bc651557d25c5cb9df7
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