Instructions to use FalconRR/es_pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use FalconRR/es_pipeline with spaCy:
!pip install https://huggingface.co/FalconRR/es_pipeline/resolve/main/es_pipeline-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("es_pipeline") # Importing as module. import es_pipeline nlp = es_pipeline.load() - Notebooks
- Google Colab
- Kaggle
| Feature | Description |
|---|---|
| Name | es_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.5.1,<3.6.0 |
| Default Pipeline | transformer, textcat |
| Components | transformer, textcat |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | Falcon Restrepo Ramos |
Label Scheme
View label scheme (2 labels for 1 components)
| Component | Labels |
|---|---|
textcat |
Col, Arg |
Accuracy
| Type | Score |
|---|---|
CATS_SCORE |
83.75 |
CATS_MICRO_P |
83.89 |
CATS_MICRO_R |
83.89 |
CATS_MICRO_F |
83.89 |
CATS_MACRO_P |
83.67 |
CATS_MACRO_R |
83.88 |
CATS_MACRO_F |
83.75 |
CATS_MACRO_AUC |
90.09 |
TRANSFORMER_LOSS |
4738.91 |
TEXTCAT_LOSS |
274.59 |
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