Instructions to use Zlovoblachko/en_L1_RuleGen_xlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use Zlovoblachko/en_L1_RuleGen_xlm with spaCy:
!pip install https://huggingface.co/Zlovoblachko/en_L1_RuleGen_xlm/resolve/main/en_L1_RuleGen_xlm-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_L1_RuleGen_xlm") # Importing as module. import en_L1_RuleGen_xlm nlp = en_L1_RuleGen_xlm.load() - Notebooks
- Google Colab
- Kaggle
| Feature | Description |
|---|---|
| Name | en_L1_RuleGen_xlm |
| Version | 0.0.0 |
| spaCy | >=3.4.4,<3.5.0 |
| Default Pipeline | transformer, spancat |
| Components | transformer, spancat |
| 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 |
|---|---|
spancat |
Word form transmission, Copying expression, Tense semantics, Synonyms, Transliteration |
Accuracy
| Type | Score |
|---|---|
SPANS_SC_F |
77.57 |
SPANS_SC_P |
86.53 |
SPANS_SC_R |
70.28 |
TRANSFORMER_LOSS |
3103.58 |
SPANCAT_LOSS |
195497.89 |
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