Instructions to use Jeevesh8/init_bert_ft_qqp-38 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-38 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-38")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-38") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-38") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 318eb6c861d90e7652890b0bdc4ae5809810920add6047cdd82da19f37df4cd2
- Size of remote file:
- 438 MB
- SHA256:
- b4389f59ccaf0511a334f18afa8ada1f2cf4d40e870b365601b57a396ad27b3d
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