Instructions to use Jeevesh8/roberta_base_qqp_ft_69 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/roberta_base_qqp_ft_69 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/roberta_base_qqp_ft_69")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/roberta_base_qqp_ft_69") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/roberta_base_qqp_ft_69") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d22c58f2d9fc26ff52cb5cffed6a684e8c765347a7c6e6a0cebf567636774a37
- Size of remote file:
- 499 MB
- SHA256:
- 33f11fcc9ec2e519517a0fdae1b2664f60a1de24b4168b73252adc2ee92fc2c5
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