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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7fa5bb827f58f337262d471e5217bc6a9a156cdc171a153a6efe275bf9a2d94a
- Size of remote file:
- 1.74 GB
- SHA256:
- dfcf110fb41fbbd6cba1ef5deab29ffcca93e463f931477142f3b6eb8f83455b
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