Instructions to use Jeevesh8/bert_ft_qqp-79 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-79 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-79")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-79") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-79") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 855e3a90d0a4edd43ba23251c69a66c13f90848dd8dadf1a7b0ee17e5fb10206
- Size of remote file:
- 438 MB
- SHA256:
- fdbeb133b376872edc413854c76dbd8ca5826c64908f19c165f40c904fa38523
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