Instructions to use zentrum-lexikographie/de_dwds_ner_dist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use zentrum-lexikographie/de_dwds_ner_dist with spaCy:
!pip install https://huggingface.co/zentrum-lexikographie/de_dwds_ner_dist/resolve/main/de_dwds_ner_dist-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("de_dwds_ner_dist") # Importing as module. import de_dwds_ner_dist nlp = de_dwds_ner_dist.load() - Notebooks
- Google Colab
- Kaggle
| Feature | Description |
|---|---|
| Name | de_dwds_ner_dist |
| Version | 0.0.3 |
| spaCy | >=3.7.1,<3.8.0 |
| Default Pipeline | transformer, ner |
| Components | transformer, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (4 labels for 1 components)
| Component | Labels |
|---|---|
ner |
LOC, MISC, ORG, PER |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
87.71 |
ENTS_P |
88.23 |
ENTS_R |
87.19 |
TRANSFORMER_LOSS |
20672.13 |
NER_LOSS |
130487.36 |
- Downloads last month
- 4
Evaluation results
- NER Precisionself-reported0.882
- NER Recallself-reported0.872
- NER F Scoreself-reported0.877