Instructions to use clulab/roberta-timex-semeval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clulab/roberta-timex-semeval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="clulab/roberta-timex-semeval")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("clulab/roberta-timex-semeval") model = AutoModelForTokenClassification.from_pretrained("clulab/roberta-timex-semeval") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 297b2a737386d92468d6308eb17f172a641eb5595cc3cc2dd3b6c4002e5de93d
- Size of remote file:
- 496 MB
- SHA256:
- 50ebe257bdfea17d4f6fba7e5c31f90ec8120fda0088cb6c60367ecab6f4e36d
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