Instructions to use Jeevesh8/init_bert_ft_qqp-17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-17 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-17")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-17") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-17") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e872f3f37fb4d529b3c8f4afc3e4a04c58da3feb51682f434830d2b0de65231a
- Size of remote file:
- 438 MB
- SHA256:
- a2c3c60778516cda6ee1a30d5034ff69f3b2436ea109e40bd9d3cbb27014422e
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