Instructions to use Jeevesh8/init_bert_ft_qqp-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-10") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a410b77026134a7386df10a091ae6d4ac1353838ff6f130a873078509584a62
- Size of remote file:
- 438 MB
- SHA256:
- b2cba8b91414d607e3ce5a327b5fd0a26dc2816d83df2ffbd43cf923ac5f916d
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