Token Classification
spaCy
English
named-entity-recognition
ner
nlp
nigeria
road-traffic-crash
road-safety
information-extraction
data-anonymization
privacy
Instructions to use pidakwo/rtc-ner-extended with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use pidakwo/rtc-ner-extended with spaCy:
!pip install https://huggingface.co/pidakwo/rtc-ner-extended/resolve/main/rtc-ner-extended-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("rtc-ner-extended") # Importing as module. import rtc-ner-extended nlp = rtc-ner-extended.load() - Notebooks
- Google Colab
- Kaggle
Download ner/model from pidakwo/rtc-ner-extended: direct link, hf CLI and curl.
- Browser
- Download file 137 kB
-
https://huggingface.co/pidakwo/rtc-ner-extended/resolve/main/ner/model
- Command line
-
hf download hf://pidakwo/rtc-ner-extended/ner/model
-
curl -L -o model https://huggingface.co/pidakwo/rtc-ner-extended/resolve/main/ner/model
137 kB
- Xet hash:
- cd5f2de40dd51f0d338628a57bdec836bdade48bcb4a20f6aa13f7f5f23fba8f
- Size of remote file:
- 137 kB
- SHA256:
- 0f2650a1291c8f1217b1dc4af364cf19a069c49c74125ceb1b9c9cc96f6aa0d4
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