Instructions to use Delicalib/ru_patents_rel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use Delicalib/ru_patents_rel with spaCy:
!pip install https://huggingface.co/Delicalib/ru_patents_rel/resolve/main/ru_patents_rel-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("ru_patents_rel") # Importing as module. import ru_patents_rel nlp = ru_patents_rel.load() - Notebooks
- Google Colab
- Kaggle
| Feature | Description |
|---|---|
| Name | ru_patents_rel |
| Version | 1.0.0 |
| spaCy | >=3.8.5,<3.9.0 |
| Default Pipeline | transformer, relation_extractor |
| Components | transformer, relation_extractor |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (5 labels for 1 components)
| Component | Labels |
|---|---|
relation_extractor |
PART-OF, LOCATED-AT, CONNECTED-WITH, IN-MANNER-OF, ATTRIBUTE-FOR |
Accuracy
| Type | Score |
|---|---|
REL_MICRO_P |
56.34 |
REL_MICRO_R |
21.41 |
REL_MICRO_F |
31.03 |
REL_MACRO_F |
22.09 |
REL_WEIGHTED_F |
29.80 |
F1_PART-OF |
46.48 |
F1_LOCATED-AT |
20.86 |
F1_CONNECTED-WITH |
13.81 |
F1_IN-MANNER-OF |
11.96 |
F1_ATTRIBUTE-FOR |
17.36 |
F1_MACRO |
0.00 |
F1_WEIGHTED |
0.00 |
TRANSFORMER_LOSS |
0.77 |
RELATION_EXTRACTOR_LOSS |
111.45 |
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