Instructions to use Jeevesh8/init_bert_ft_qqp-85 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-85 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-85")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-85") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-85") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25bd2d1f528fa760935a30346db2f247854739299bba7c7a875ae6abeaa1837a
- Size of remote file:
- 438 MB
- SHA256:
- e2d52b294c570b2d7907d397a1f04d8b5edfb600aecce3f545618a0329527ead
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