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en_stonk_pipeline
FriendlyUser/en_stonk_pipeline
en_stonk_pipeline is a machine learning model from FriendlyUser. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for spacy.
pipeline to extract stonk names, need to adjust for general use as some stonk names are very short. Based on the standard spacy pipeline, but added a pipe and wanted to distribute it easily
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.whl13.5 MB · 38%
At a glance
- Library
- spacy
- Access
- Public
- Created
- Sep 10, 2022
- Updated
- Sep 15, 2022
- SHA
- 40c4bf07
Model card
From the Hugging Face model README
pipeline to extract stonk names, need to adjust for general use as some stonk names are very short. Based on the standard spacy pipeline, but added a pipe and wanted to distribute it easily
| Feature | Description |
|---|---|
| Name | en_stonk_pipeline |
| Version | 0.0.1 |
| spaCy | >=3.4.1,<3.5.0 |
| Default Pipeline | entity_ruler |
| Components | entity_ruler |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | OntoNotes 5 (Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston)<br />ClearNLP Constituent-to-Dependency Conversion (Emory University)<br />WordNet 3.0 (Princeton University) |
| License | n/a |
| Author | FriendlyUser |
Label Scheme
<details> <summary>View label scheme (8 labels for 1 components)</summary>| Component | Labels |
|---|---|
entity_ruler | COMPANY, COUNTRY, DIVIDENDS, INDEX, MAYBE, STOCK, STOCK_EXCHANGE, THINGS |
Accuracy
| Type | Score |
|---|---|
TOKEN_ACC | 99.93 |
TOKEN_P | 99.57 |
TOKEN_R | 99.58 |
TOKEN_F | 99.57 |
TAG_ACC | 97.26 |
SENTS_P | 91.92 |
SENTS_R | 88.90 |
SENTS_F | 90.39 |
DEP_UAS | 91.66 |
DEP_LAS | 89.78 |
ENTS_P | 85.65 |
ENTS_R | 83.49 |
ENTS_F | 84.56 |
- Library
- spacy
- Languages
- en
- Created
- Sep 10, 2022
- Updated
- Sep 15, 2022