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:
- ab22a28fc0592a573b8bbbc88af533e8291d90e50e8ef978cb51c639011df572
- Size of remote file:
- 301 kB
- SHA256:
- 29fe2752bc8389f09e76e9b7210cc5d5f065a83041e63134e17676c6a5e02405
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