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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89d9202de12b7ace4eafa5f26f7b94249295cdd9b718131cd1cb61960de471a1
- Size of remote file:
- 285 kB
- SHA256:
- a5115c0b5c5b02b188c6824bc46f098fd33df31c794abc052b34123cff26162b
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