Instructions to use Jeevesh8/init_bert_ft_qqp-46 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-46 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-46")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-46") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-46") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- edccc79754114b3b96e7ed0c775b8e4431722fba5ab5fb1b52a7f49159bfe410
- Size of remote file:
- 438 MB
- SHA256:
- cfd5a53cfee3a410d829247d4ae836c176a6b27c115d3f7d6c216ffefb1ed0fe
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