Instructions to use andreids/en_classification_of_services with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use andreids/en_classification_of_services with spaCy:
!pip install https://huggingface.co/andreids/en_classification_of_services/resolve/main/en_classification_of_services-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_classification_of_services") # Importing as module. import en_classification_of_services nlp = en_classification_of_services.load() - Notebooks
- Google Colab
- Kaggle
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Download README.md from andreids/en_classification_of_services: direct link, hf CLI and curl.
- Browser
- Download file 973 Bytes
-
https://huggingface.co/andreids/en_classification_of_services/resolve/main/README.md
- Command line
-
hf download hf://andreids/en_classification_of_services/README.md
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curl -L -o README.md https://huggingface.co/andreids/en_classification_of_services/resolve/main/README.md
973 Bytes
metadata
tags:
- spacy
- text-classification
language:
- en
model-index:
- name: en_classification_of_services
results: []
| Feature | Description |
|---|---|
| Name | en_classification_of_services |
| Version | 0.0.0 |
| spaCy | >=3.4.3,<3.5.0 |
| Default Pipeline | textcat |
| Components | textcat |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (2 labels for 1 components)
| Component | Labels |
|---|---|
textcat |
other, service |
Accuracy
| Type | Score |
|---|---|
CATS_SCORE |
99.89 |
CATS_MICRO_P |
99.98 |
CATS_MICRO_R |
99.98 |
CATS_MICRO_F |
99.98 |
CATS_MACRO_P |
99.99 |
CATS_MACRO_R |
99.80 |
CATS_MACRO_F |
99.89 |
CATS_MACRO_AUC |
99.90 |
CATS_MACRO_AUC_PER_TYPE |
0.00 |
TEXTCAT_LOSS |
0.00 |