Instructions to use hf-tiny-model-private/tiny-random-GLPNModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-GLPNModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-GLPNModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-GLPNModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-GLPNModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a5abda6fccc5541540d1b3fe7336158ff90b138b8ca6c149410f9c3038d6780
- Size of remote file:
- 3.01 MB
- SHA256:
- f0967bd34f98f635741e56ff3af500dfbf51764b7a620b114d9d0f478c5d900d
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