Instructions to use Jeevesh8/init_bert_ft_qqp-14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-14")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-14") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-14") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a7f79763365b8c01234af1f4185f64a37b6741d22388b2f8b82b120fb183151
- Size of remote file:
- 438 MB
- SHA256:
- 1d7cf673617df5bcb4facb3ec2ab53ab894214772595caf210e68edceaaeab47
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