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
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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 | |