Instructions to use Jeevesh8/init_bert_ft_qqp-78 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-78 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-78")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-78") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-78") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3af5912113ca21315bc228852322242a1623e919875e4200329b973e33caa81b
- Size of remote file:
- 438 MB
- SHA256:
- 8bc5850b92e2037089f743103777015439c7014b162aa33d6775f8ab6dd6f8ac
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