Instructions to use Jeevesh8/init_bert_ft_qqp-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-1") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 669c9b01d2e1b0b59cbafc583d16ffd6081516542a15849752bec5410bfd4f48
- Size of remote file:
- 438 MB
- SHA256:
- 6fbc0ce4e6ea76086d7377d8c8fab222dfd2e10088763647eebd90464278af07
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