Instructions to use hf-internal-testing/tiny-random-FocalNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FocalNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-FocalNetModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-FocalNetModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-FocalNetModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac5e396e626c7cd6044c8a6c368f117fa24c8c87b2b3cb2a8a4d6874bf858740
- Size of remote file:
- 301 kB
- SHA256:
- 3e8d390a8902316a88be38fdf5ab39c264f5306fcf5c76f8c1a451efe722dc35
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