Instructions to use dg845/univnet-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dg845/univnet-dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dg845/univnet-dev")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("dg845/univnet-dev") model = AutoModel.from_pretrained("dg845/univnet-dev") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5948a25e50bce341fb3617f3f6046d5da34d8b7841f8beb7dd83f48c1a4d475c
- Size of remote file:
- 59.2 MB
- SHA256:
- 9e4fc60886a2897afb1974a9f1c3137151e5519ca6a9fdb6d88a353ed18146bb
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