Instructions to use Jeevesh8/init_bert_ft_qqp-37 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-37 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-37")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-37") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-37") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4160266327af134a28296e877499fb53b7cf6bdaadc0aaaa6a2e3a1dc802f47d
- Size of remote file:
- 438 MB
- SHA256:
- 71da4c4a4d93ebe632fbe62496cf147ea706bcb679add19e23facc65f5ba978d
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