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 ner/moves from pidakwo/rtc-ner: direct link, hf CLI and curl.
- Browser
- Download file 544 Bytes
-
https://huggingface.co/pidakwo/rtc-ner/resolve/main/ner/moves
- Command line
-
hf download hf://pidakwo/rtc-ner/ner/moves
-
curl -L -o moves https://huggingface.co/pidakwo/rtc-ner/resolve/main/ner/moves
544 Bytes
| ��moves�{"0":{},"1":{"ROAD":2906,"HOSPITAL":1966,"STATE":1104,"CASUALTY":959,"TOWN":817,"LGA":815,"LANDMARK":788,"INJURED":439,"SUBURB":51},"2":{"ROAD":2906,"HOSPITAL":1966,"STATE":1104,"CASUALTY":959,"TOWN":817,"LGA":815,"LANDMARK":788,"INJURED":439,"SUBURB":51},"3":{"ROAD":2906,"HOSPITAL":1966,"STATE":1104,"CASUALTY":959,"TOWN":817,"LGA":815,"LANDMARK":788,"INJURED":439,"SUBURB":51},"4":{"ROAD":2906,"HOSPITAL":1966,"STATE":1104,"CASUALTY":959,"TOWN":817,"LGA":815,"LANDMARK":788,"INJURED":439,"SUBURB":51,"":1},"5":{"":1}}�cfg��neg_key� |