Instructions to use tedad09/DuplicateCrossEncoder-Riscaldamento2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tedad09/DuplicateCrossEncoder-Riscaldamento2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tedad09/DuplicateCrossEncoder-Riscaldamento2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tedad09/DuplicateCrossEncoder-Riscaldamento2") model = AutoModelForSequenceClassification.from_pretrained("tedad09/DuplicateCrossEncoder-Riscaldamento2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 789f2413752a8008c44ff6618291bce2acba83ebe9b6b9c4bcf66f58429b458f
- Size of remote file:
- 133 MB
- SHA256:
- a23fc69d5c1e3d4b3bc3d25a737fa1b9ddf527f06822004540b1e092ab68d632
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