Instructions to use Jeevesh8/roberta_base_qqp_ft_41 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/roberta_base_qqp_ft_41 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/roberta_base_qqp_ft_41")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/roberta_base_qqp_ft_41") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/roberta_base_qqp_ft_41") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c60826ba2bcfa3c09ce02d25d04bfc883666d23b17868ac1b1d53e7fa7e26751
- Size of remote file:
- 499 MB
- SHA256:
- bd3c32ecb1967c8c3cc130c6d0c17bb8050ec529b999ff02539e4249b0507804
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