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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jimnoneill/CarD-T") model = AutoModelForTokenClassification.from_pretrained("jimnoneill/CarD-T", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-3405/training_args.bin from jimnoneill/CarD-T: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/jimnoneill/CarD-T/resolve/main/checkpoint-3405/training_args.bin
- Command line
-
hf download hf://jimnoneill/CarD-T/checkpoint-3405/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jimnoneill/CarD-T/resolve/main/checkpoint-3405/training_args.bin
5.43 kB
- Xet hash:
- 68ec716be80bdd7bb5fec8f6001ba111e89e190123e2becfebea679bcfb492b3
- Size of remote file:
- 5.43 kB
- SHA256:
- 6fbf6ee382bdf4fc7a704ade5bbd728f43b83dd5b0a0779f6ffdaf51f9e4d6d2
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