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:
- 705a874b12796b72adc98e584838039c8e9e778027e7ec8e9986b44af44c410d
- Size of remote file:
- 418 kB
- SHA256:
- d830f0ffb5843c2a6725965b5dbd9282bb01d8fce86854f4b3726f7c313bff03
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