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:
- 0ced619af313fea073c4edd20f846c59e05f6fc9c25d738885cd8239f48a2510
- Size of remote file:
- 301 kB
- SHA256:
- d683019d4ece71b0a21067cb51052ef76711ee5a83a0a936f0db303da6d48acc
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