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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add metadata, link to paper and code
#1
by nielsr HF Staff - opened
This PR adds metadata to the model card, including the license (mit), library name (transformers) and pipeline tag (feature-extraction). It also adds a link to the paper and the code repository. Some minor improvements were made to the model card content.
fondress changed pull request status to merged