Instructions to use Jeevesh8/init_bert_ft_qqp-68 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-68 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-68")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-68") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-68") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9bdcc23b5a34616a660ecda98df6ad51d3e1369fbf45f3845d1780fb1311f8ba
- Size of remote file:
- 438 MB
- SHA256:
- de3031e9a9251fe5c8bac4adc5b328a98f86c8a165d75a3ba8e1a2113db8d2e2
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