Instructions to use Akshayextreme/SemEval_2015_PIT_crossencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akshayextreme/SemEval_2015_PIT_crossencoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Akshayextreme/SemEval_2015_PIT_crossencoder")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Akshayextreme/SemEval_2015_PIT_crossencoder") model = AutoModelForSequenceClassification.from_pretrained("Akshayextreme/SemEval_2015_PIT_crossencoder") - Notebooks
- Google Colab
- Kaggle
Commit ·
4684351
1
Parent(s): 3181018
Pushing trained model
Browse files- tokenizer.json +4 -4
tokenizer.json
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