Instructions to use tedad09/DuplicateCrossEncoder-SecondTrain-20Epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tedad09/DuplicateCrossEncoder-SecondTrain-20Epochs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tedad09/DuplicateCrossEncoder-SecondTrain-20Epochs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tedad09/DuplicateCrossEncoder-SecondTrain-20Epochs") model = AutoModelForSequenceClassification.from_pretrained("tedad09/DuplicateCrossEncoder-SecondTrain-20Epochs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53038c2044cfbdbae6572ff39a74bf2aca4f854caf4c78a2e205b9453297587b
- Size of remote file:
- 133 MB
- SHA256:
- 67ddca8e450890f6d19a1980645b72902d420cdb776f8c182ae05e3fd11b23ee
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