Instructions to use hf-internal-testing/tiny-random-GLPNModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GLPNModel 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-GLPNModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-GLPNModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-GLPNModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 364f49ac328731a54619e97bfbd8a330632f197bc4e89236529ab9af1bf03176
- Size of remote file:
- 3.05 MB
- SHA256:
- f6a2a2d81128a4b644396a439e662ebb232e3336baa7a6b67199b766f66e0971
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