Instructions to use Jeevesh8/init_bert_ft_qqp-39 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-39 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-39")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-39") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-39") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 798e372b692ce1046be4bab253aaba04a807875a230875260ede121d3dc034f5
- Size of remote file:
- 438 MB
- SHA256:
- 6ec70cc7abb72c1023ee9b6749e12db1d913273b1de778c0decbe95d7d467d4a
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