Instructions to use Jeevesh8/init_bert_ft_qqp-23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-23 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-23")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-23") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-23") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3f768725d7493524fbe32c72bd7315d79e34aeef8750310bc8d705edab4b05f
- Size of remote file:
- 438 MB
- SHA256:
- 160f78d981a99f92c5bf1cb5cfe5cf326392357ec4608de34c159145644cc40e
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