Instructions to use Cogoport/en_Spacy_Custom_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use Cogoport/en_Spacy_Custom_ner with spaCy:
!pip install https://huggingface.co/Cogoport/en_Spacy_Custom_ner/resolve/main/en_Spacy_Custom_ner-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_Spacy_Custom_ner") # Importing as module. import en_Spacy_Custom_ner nlp = en_Spacy_Custom_ner.load() - Notebooks
- Google Colab
- Kaggle
Download tok2vec/model from Cogoport/en_Spacy_Custom_ner: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/Cogoport/en_Spacy_Custom_ner/resolve/main/tok2vec/model
- Command line
-
hf download hf://Cogoport/en_Spacy_Custom_ner/tok2vec/model
-
curl -L -o model https://huggingface.co/Cogoport/en_Spacy_Custom_ner/resolve/main/tok2vec/model
34.4 MB
- Xet hash:
- 51f7a2ab17f16aa06e3f4fbb0acb6f0424534dc5706b9bd2745292aaa67dba1f
- Size of remote file:
- 34.4 MB
- SHA256:
- 4e2f3e2fab9f568a5c3e23cbe9aa9f9e7e51da3c44d61ed32c617696964b45eb
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