Instructions to use Jeevesh8/init_bert_ft_qqp-57 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-57 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-57")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-57") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-57") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95be633b8088704cc6f55e3d271d122a92f8439361400ed692aa3bb790b2a8a8
- Size of remote file:
- 438 MB
- SHA256:
- 3ec6c27a7a9af3f843efadd2d4e2a995212775f6ba4072c59100e898ab6e3511
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