Instructions to use Jeevesh8/init_bert_ft_qqp-79 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-79 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-79")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-79") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-79") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a055fd8875c8555311b4dff95258c801e27da8e3b7d4f32df5857648763eee6e
- Size of remote file:
- 438 MB
- SHA256:
- cd43463e0135409e2591efed21ac89690eb723502e5200d4b9070c2b0e30483d
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