Instructions to use Jeevesh8/init_bert_ft_qqp-34 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-34 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-34")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-34") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-34") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7f491f838e655266af044c0bf3fa48e3d99a3b90318e873604d06b055461840
- Size of remote file:
- 438 MB
- SHA256:
- 82a350470aaee720f1d39bc59448a883cbb57868a8a66a82a6ac9253496d9409
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