Instructions to use osanseviero/fashion_brands_patterns with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use osanseviero/fashion_brands_patterns with spaCy:
!pip install https://huggingface.co/osanseviero/fashion_brands_patterns/resolve/main/fashion_brands_patterns-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("fashion_brands_patterns") # Importing as module. import fashion_brands_patterns nlp = fashion_brands_patterns.load() - Notebooks
- Google Colab
- Kaggle
| Feature | Description |
|---|---|
| Name | en_ner_fashion |
| Version | 0.0.0 |
| spaCy | >=3.1.0,<3.2.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (1 labels for 1 components)
| Component | Labels |
|---|---|
ner |
FASHION_BRAND |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
0.00 |
ENTS_P |
0.00 |
ENTS_R |
0.00 |
TOK2VEC_LOSS |
1043.55 |
NER_LOSS |
1414323.43 |
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Space using osanseviero/fashion_brands_patterns 1
Evaluation results
- NER Precisionself-reported0.000
- NER Recallself-reported0.000
- NER F Scoreself-reported0.000