Instructions to use Zlovoblachko/L1_Copying_expression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use Zlovoblachko/L1_Copying_expression with spaCy:
!pip install https://huggingface.co/Zlovoblachko/L1_Copying_expression/resolve/main/L1_Copying_expression-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("L1_Copying_expression") # Importing as module. import L1_Copying_expression nlp = L1_Copying_expression.load() - Notebooks
- Google Colab
- Kaggle
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Download README.md from Zlovoblachko/L1_Copying_expression: direct link, hf CLI and curl.
- Browser
- Download file 806 Bytes
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https://huggingface.co/Zlovoblachko/L1_Copying_expression/resolve/main/README.md
- Command line
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hf download hf://Zlovoblachko/L1_Copying_expression/README.md
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curl -L -H "Authorization: Bearer $HF_TOKEN" -o README.md https://huggingface.co/Zlovoblachko/L1_Copying_expression/resolve/main/README.md
806 Bytes
| 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`** | `Copying expression` | | |
| </details> | |
| ### Accuracy | |
| | Type | Score | | |
| | --- | --- | | |
| | `SPANS_SC_F` | 61.54 | | |
| | `SPANS_SC_P` | 80.00 | | |
| | `SPANS_SC_R` | 50.00 | | |
| | `TRANSFORMER_LOSS` | 2250.61 | | |
| | `SPANCAT_LOSS` | 59989.48 | |