Instructions to use Jeevesh8/init_bert_ft_qqp-9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-9")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-9") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-9") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9ad94f03c6006d668b92d83ec7f2b7c8d3c428c397db3812671d3f1d99f89a1
- Size of remote file:
- 438 MB
- SHA256:
- 3bbc89f000e657ea6a4ff4a9b5bb4064ead3415a38ee3d56a935968b6a44f679
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