Instructions to use covalenthq/cryptoNER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use covalenthq/cryptoNER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="covalenthq/cryptoNER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("covalenthq/cryptoNER") model = AutoModelForTokenClassification.from_pretrained("covalenthq/cryptoNER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e83cd5627624d34568e5c6ab950c887c949ebc140ae9048940429c8b31bfb764
- Size of remote file:
- 4.54 kB
- SHA256:
- 7f97e9408fb2064ad880c190e6b552ec42e7b3bf8ef5ac91969fe41997c5eb5b
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