spaCy
English
b2b_ecommerce_ner
named-entity-recognition
b2b
ecommerce
order-processing
product-extraction
Eval Results (legacy)
Instructions to use Purva17/b2b-ecomm-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use Purva17/b2b-ecomm-ner with spaCy:
!pip install https://huggingface.co/Purva17/b2b-ecomm-ner/resolve/main/b2b-ecomm-ner-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("b2b-ecomm-ner") # Importing as module. import b2b-ecomm-ner nlp = b2b-ecomm-ner.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6198d73f47368cc80146bc654b640a90ad0a05eb54c1fad81ec53e6e4a7874b3
- Size of remote file:
- 320 kB
- SHA256:
- e0098910535a863d430082ece57455d5fa071cd4ca3a0054e80582076c752b1e
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