Instructions to use hf-internal-testing/tiny-random-UnivNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UnivNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-UnivNetModel")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-UnivNetModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-UnivNetModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0ac31ca4335c781bb3b154ce343ba1799b9cd688ba6b70d63798675f645e5df
- Size of remote file:
- 535 kB
- SHA256:
- c839be05c8b295252fd5554c21741b3a8af5daad3f3b475af13f8240c1977f9a
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