Instructions to use MilosKosRad/TextualEntailment_DeBERTa_preprocessedSciFACT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MilosKosRad/TextualEntailment_DeBERTa_preprocessedSciFACT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MilosKosRad/TextualEntailment_DeBERTa_preprocessedSciFACT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MilosKosRad/TextualEntailment_DeBERTa_preprocessedSciFACT") model = AutoModelForSequenceClassification.from_pretrained("MilosKosRad/TextualEntailment_DeBERTa_preprocessedSciFACT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e56bb9c2ffb904b809e69688907eb40195f7bb28736cfe0cdb8a29120cf1cbf0
- Size of remote file:
- 3.96 kB
- SHA256:
- cddc25b8c11e6cc20929c8c43663d2d5d2c63d5540302c9cf202fbb4c0c8b8e4
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