Instructions to use ModelTC/roberta-base-qqp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/roberta-base-qqp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/roberta-base-qqp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/roberta-base-qqp") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/roberta-base-qqp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04b0cab9bd9f8482d82f7f5d6b86c66e66732f6eaceea0c6160b30eed45f96ae
- Size of remote file:
- 997 MB
- SHA256:
- aec343a5d7621f55ed3aab706b2cb04d8702ec27f96f1f559a45d7bed50a567e
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