Instructions to use Jeevesh8/init_bert_ft_qqp-70 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-70 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-70")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-70") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-70") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 020e5f43958bede76139d11aee3f3f64fbae589138dbcc3b235d38b2d9a0de63
- Size of remote file:
- 438 MB
- SHA256:
- d5b51d46fa0ca51e90855db57253e2b137a8b59367e7906b05265e5f5d577dbf
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