Instructions to use Jeevesh8/init_bert_ft_qqp-87 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-87 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-87")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-87") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-87") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90531a920aa4d57fdabe2613af2829ce4aa9b6a56a717b6a2ac1d14acb1463fe
- Size of remote file:
- 438 MB
- SHA256:
- c7bad54ea3d830dcdaed8c62ddbd510d357e2a860e13cc63be5e55f6c26ceeec
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