Instructions to use Zlovoblachko/sentiment_parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use Zlovoblachko/sentiment_parser with spaCy:
!pip install https://huggingface.co/Zlovoblachko/sentiment_parser/resolve/main/sentiment_parser-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("sentiment_parser") # Importing as module. import sentiment_parser nlp = sentiment_parser.load() - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - spacy | |
| language: | |
| - en | |
| model-index: | |
| - name: en_pipeline | |
| results: [] | |
| | Feature | Description | | |
| | --- | --- | | |
| | **Name** | `en_pipeline` | | |
| | **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 | |
| <details> | |
| <summary>View label scheme (1 labels for 1 components)</summary> | |
| | Component | Labels | | |
| | --- | --- | | |
| | **`spancat`** | `Collocation calque` | | |
| </details> | |
| ### Accuracy | |
| | Type | Score | | |
| | --- | --- | | |
| | `SPANS_SC_F` | 78.65 | | |
| | `SPANS_SC_P` | 79.55 | | |
| | `SPANS_SC_R` | 77.78 | | |
| | `TRANSFORMER_LOSS` | 7535.29 | | |
| | `SPANCAT_LOSS` | 148493.75 | |