Instructions to use mpi-inno-comp/en_abstract_cleaner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use mpi-inno-comp/en_abstract_cleaner with spaCy:
!pip install https://huggingface.co/mpi-inno-comp/en_abstract_cleaner/resolve/main/en_abstract_cleaner-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_abstract_cleaner") # Importing as module. import en_abstract_cleaner nlp = en_abstract_cleaner.load() - Notebooks
- Google Colab
- Kaggle
spaCy NER model that identifies and removes clutter from academic paper abstracts.
| Feature | Description |
|---|---|
| Name | en_abstract_cleaner |
| Version | 1.0.0 |
| spaCy | >=3.8.7,<3.9.0 |
| Default Pipeline | ner, doc_cleaner |
| Components | ner, doc_cleaner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | MIT |
| Author | Michael A. Rose, Nils A. Herrmann, Sebastian Erhardt |
Label Scheme
View label scheme (1 labels for 1 components)
| Component | Labels |
|---|---|
ner |
REMOVE |
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