Instructions to use Jeevesh8/bert_ft_qqp-95 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-95 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-95")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-95") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-95") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d518d3865991a6b0bcd599bbb74a487dbfa4cdf2f1df707e859708bbfe794705
- Size of remote file:
- 438 MB
- SHA256:
- 5e373c76697865df8275c9c70450f26c776613cf9d5d43fd45d6a9472e171ebe
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