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xx_LeetSpeakNER_mstsb_mpnet
Huertas97/xx_LeetSpeakNER_mstsb_mpnet
xx_LeetSpeakNER_mstsb_mpnet is a token classification model from Huertas97. Use it when you need labels on individual words, such as names. It is set up for spacy.
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At a glance
- Task
- Token Classification
- Library
- spacy
- Access
- Public
- Created
- Dec 2, 2022
- Updated
- Sep 21, 2024
- SHA
- 0a7b0a5a
Model card
From the Hugging Face model README
| Feature | Description |
|---|---|
| Name | xx_LeetSpeakNER_mstsb_mpnet |
| Version | 0.0.0 |
| spaCy | >=3.4.3,<3.5.0 |
| Default Pipeline | transformer, ner |
| Components | transformer, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Usage
### UPDATE INSTALLATION WITH PACKAGE NAME
!pip install "xx_LeetSpeakNER_mstsb_mpnet @ https://huggingface.co/Huertas97/xx_LeetSpeakNER_mstsb_mpnet/resolve/main/xx_LeetSpeakNER_mstsb_mpnet-any-py3-none-any.whl"
# Using spacy.load().
import spacy
nlp = spacy.load("xx_LeetSpeakNER_mstsb_mpnet")
# Importing as module.
import xx_LeetSpeakNER_mstsb_mpnet
nlp = xx_LeetSpeakNER_mstsb_mpnet.load()
Label Scheme
<details> <summary>View label scheme (4 labels for 1 components)</summary>| Component | Labels |
|---|---|
ner | INV_CAMO, LEETSPEAK, MIX, PUNCT_CAMO |
Accuracy
| Type | Score |
|---|---|
ENTS_F | 91.42 |
ENTS_P | 91.24 |
ENTS_R | 91.60 |
TRANSFORMER_LOSS | 396910.59 |
NER_LOSS | 373097.06 |
- Task
- Token Classification
- Library
- spacy
- Languages
- multilingual
- Created
- Dec 2, 2022
- Updated
- Sep 21, 2024