Instructions to use Jeevesh8/init_bert_ft_qqp-27 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-27 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-27")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-27") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-27") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5bf3690ab46bf97652e1ba2a2b1133851e7ae02ae53ff12fece1dc390ac0f78d
- Size of remote file:
- 438 MB
- SHA256:
- e5f42116feb681b2ad86d96fa393888c336f6c41fd2afc8dc3544c0c7a8207df
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