Instructions to use fondress/PDeepPP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fondress/PDeepPP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fondress/PDeepPP")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fondress/PDeepPP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a0a0aaee5c81e9ba883ec7e4ca6310b75f976afdbd1f1be1947542205dcba14
- Size of remote file:
- 98.3 MB
- SHA256:
- 82d758ae5118ac788874e3206f8c1b420066b508b8daf20c870f15b93baf37e1
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