Instructions to use tedad09/DuplicateCrossEncoder-SecondTrain-10Epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tedad09/DuplicateCrossEncoder-SecondTrain-10Epochs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tedad09/DuplicateCrossEncoder-SecondTrain-10Epochs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tedad09/DuplicateCrossEncoder-SecondTrain-10Epochs") model = AutoModelForSequenceClassification.from_pretrained("tedad09/DuplicateCrossEncoder-SecondTrain-10Epochs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60a673f78682dd9e3660e39fd894430bab1ad3deab80ac26e7840ca45ef2e8be
- Size of remote file:
- 133 MB
- SHA256:
- 7791a8210854b9473e291ba138d2927fb68424143448a12e3b44857e9d7d63c9
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