Instructions to use Jeevesh8/init_bert_ft_qqp-31 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-31 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-31")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-31") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-31") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9f8757b5e6c99cbc2c2cffca7341be18fa6f5c24de75436e7c03fb4c51c8f1f
- Size of remote file:
- 438 MB
- SHA256:
- 523ae1bf4d135b8c2a0d19d821f64d3a6da02816387b0b6135f4ef1f9b13e037
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