Instructions to use noahjadallah/cause-effect-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use noahjadallah/cause-effect-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="noahjadallah/cause-effect-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("noahjadallah/cause-effect-detection") model = AutoModelForTokenClassification.from_pretrained("noahjadallah/cause-effect-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3dce00c739db3a2eda3b7fe6e02a665dfc7fb96a0e6e17b9bcd744e24064fa29
- Size of remote file:
- 436 MB
- SHA256:
- 8288362d763f5b30bd259dd1a04dc2555d2c48564b243644ba8ddcf87ee02b7d
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