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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01f22dcaf477b054c02b7b3a163b559bb604cd9dfe4f87d1298d4261f52935fa
- Size of remote file:
- 3.05 MB
- SHA256:
- 030d139eb52c02711c37312394b0f6648751e82a5bffe9580a055542f56f38ce
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