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:
- 740885e48b388b1695895da128cbb626fe3dc2e79b0afdc59797c11822410b92
- Size of remote file:
- 301 kB
- SHA256:
- 3da69de68821e8e235d797229d115573331c2c4fa80b3644f1750d469fb66770
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