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
Update tiny models for UnivNetModel
Browse files- config.json +1 -1
config.json
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"torch_dtype": "float32",
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"transformers_version": "4.
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}
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4
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],
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"torch_dtype": "float32",
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"transformers_version": "4.39.0.dev0"
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}
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