Instructions to use Jeevesh8/init_bert_ft_qqp-43 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-43 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-43")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-43") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-43") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e756bb3e94408dc353d884b79d6174ce3fe61beff313d594da075e5270c484c
- Size of remote file:
- 438 MB
- SHA256:
- 4103a4fdd7888c942d9a2dbb06fd480ce8df969b1f4deee815132e00f5484971
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