Instructions to use Jeevesh8/init_bert_ft_qqp-93 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-93 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-93")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-93") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-93") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4077cb05b8e548a57b73691ab37fdc9c8274f024ad74f1f34c17223ba918157
- Size of remote file:
- 438 MB
- SHA256:
- adac49f67497259404abb555137033d21d27a8af19808fa059e7f8bc16fec8a0
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