Token Classification
spaCy
English
named-entity-recognition
ner
nlp
road-traffic-crash
road-safety
information-extraction
geospatial
nigeria
Instructions to use pidakwo/rtc-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use pidakwo/rtc-ner with spaCy:
!pip install https://huggingface.co/pidakwo/rtc-ner/resolve/main/rtc-ner-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("rtc-ner") # Importing as module. import rtc-ner nlp = rtc-ner.load() - Notebooks
- Google Colab
- Kaggle
Download meta.json from pidakwo/rtc-ner: direct link, hf CLI and curl.
- Browser
- Download file 1.75 kB
-
https://huggingface.co/pidakwo/rtc-ner/resolve/main/meta.json
- Command line
-
hf download hf://pidakwo/rtc-ner/meta.json
-
curl -L -o meta.json https://huggingface.co/pidakwo/rtc-ner/resolve/main/meta.json
1.75 kB
| { | |
| "lang":"en", | |
| "name":"pipeline", | |
| "version":"0.0.0", | |
| "spacy_version":">=3.6.1,<3.7.0", | |
| "description":"", | |
| "author":"", | |
| "email":"", | |
| "url":"", | |
| "license":"", | |
| "spacy_git_version":"458bc5f45", | |
| "vectors":{ | |
| "width":0, | |
| "vectors":0, | |
| "keys":0, | |
| "name":null, | |
| "mode":"default" | |
| }, | |
| "labels":{ | |
| "tok2vec":[ | |
| ], | |
| "ner":[ | |
| "CASUALTY", | |
| "HOSPITAL", | |
| "INJURED", | |
| "LANDMARK", | |
| "LGA", | |
| "ROAD", | |
| "STATE", | |
| "SUBURB", | |
| "TOWN" | |
| ] | |
| }, | |
| "pipeline":[ | |
| "tok2vec", | |
| "ner" | |
| ], | |
| "components":[ | |
| "tok2vec", | |
| "ner" | |
| ], | |
| "disabled":[ | |
| ], | |
| "performance":{ | |
| "ents_f":0.9392883802, | |
| "ents_p":0.9381212724, | |
| "ents_r":0.9404583956, | |
| "ents_per_type":{ | |
| "CASUALTY":{ | |
| "p":0.9034482759, | |
| "r":0.9018932874, | |
| "f":0.902670112 | |
| }, | |
| "TOWN":{ | |
| "p":0.913107511, | |
| "r":0.9295352324, | |
| "f":0.9212481426 | |
| }, | |
| "LGA":{ | |
| "p":0.9545454545, | |
| "r":0.9692307692, | |
| "f":0.9618320611 | |
| }, | |
| "STATE":{ | |
| "p":0.947008547, | |
| "r":0.9502572899, | |
| "f":0.948630137 | |
| }, | |
| "ROAD":{ | |
| "p":0.9763313609, | |
| "r":0.9786476868, | |
| "f":0.9774881517 | |
| }, | |
| "INJURED":{ | |
| "p":0.9057377049, | |
| "r":0.9170124481, | |
| "f":0.9113402062 | |
| }, | |
| "LANDMARK":{ | |
| "p":0.9272727273, | |
| "r":0.8571428571, | |
| "f":0.8908296943 | |
| }, | |
| "HOSPITAL":{ | |
| "p":0.9525483304, | |
| "r":0.9592920354, | |
| "f":0.9559082892 | |
| }, | |
| "SUBURB":{ | |
| "p":0.8684210526, | |
| "r":0.9166666667, | |
| "f":0.8918918919 | |
| } | |
| }, | |
| "tok2vec_loss":4200.0542435646, | |
| "ner_loss":6021.9171480695 | |
| } | |
| } |