Instructions to use Jeevesh8/init_bert_ft_qqp-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-50")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-50") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-50") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5875a9215f08bb271b0e92e84b481bea454c6fa4100709cde40dbc5b62bc0c2
- Size of remote file:
- 438 MB
- SHA256:
- aa4a4866675139b594153f5ee006dd123c484e25c253d6e27a5fd6c897b5ebfe
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