Token Classification
spaCy
English
Named Entity Recognition Model
NER
Cryptocurrency
Crypto
Eval Results (legacy)
Instructions to use KonstIT/Crypto_NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use KonstIT/Crypto_NER with spaCy:
!pip install https://huggingface.co/KonstIT/Crypto_NER/resolve/main/Crypto_NER-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("Crypto_NER") # Importing as module. import Crypto_NER nlp = Crypto_NER.load() - Notebooks
- Google Colab
- Kaggle
Download transformer/model from KonstIT/Crypto_NER: direct link, hf CLI and curl.
- Browser
- Download file 502 MB
-
https://huggingface.co/KonstIT/Crypto_NER/resolve/main/transformer/model
- Command line
-
hf download hf://KonstIT/Crypto_NER/transformer/model
-
curl -L -o model https://huggingface.co/KonstIT/Crypto_NER/resolve/main/transformer/model
502 MB
- Xet hash:
- e8b59a68811a1eac84c2832c2717745fc1dca6e98bfc8848c1406c989fce13c5
- Size of remote file:
- 502 MB
- SHA256:
- 70e09321bc2ffb7f34d96cb0c028bee0d6ff04528ac7d61a8e11dce7751c3419
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