Instructions to use Jeevesh8/init_bert_ft_qqp-69 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-69 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-69")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-69") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-69") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1089e5e1cae85d324041cc3625525972cff139339fc96b956f19b6c45da5c284
- Size of remote file:
- 438 MB
- SHA256:
- c161208cd7af9af2361b63a54b25a7178ab20e4784c2394e868c97b4fb343f32
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