Instructions to use Jeevesh8/bert_ft_qqp_6ep-21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp_6ep-21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp_6ep-21")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp_6ep-21") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp_6ep-21") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0b47315c648bfb6d1c2f453e51c36197117b23374c27c3705b33f886d379792
- Size of remote file:
- 438 MB
- SHA256:
- 2108c10fea003fd38da0613fe634048f18794d5399a669286d5cd4127c9c5065
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