Token Classification
Transformers
TensorBoard
Safetensors
English
electra
biology
chemistry
medical
cancer
carcinogenesis
biomedical
ner
oncology
Eval Results (legacy)
Instructions to use jimnoneill/CarD-T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jimnoneill/CarD-T with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jimnoneill/CarD-T")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jimnoneill/CarD-T") model = AutoModelForTokenClassification.from_pretrained("jimnoneill/CarD-T") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b73dbadc38ffb0771e46ae21a3a7b8536461c10ece3f1e3741420c85fce73ea5
- Size of remote file:
- 2.66 GB
- SHA256:
- f27b65e1ecc59b25c4d7e5c7daf5576fa34b0dfa99c71f5de7be4333aec324da
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