Instructions to use Jeevesh8/init_bert_ft_qqp-18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-18 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-18")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-18") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-18") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 803463d1042d39c753791581b1ff423946ac10cf535c9ef6e095df9e1182ac96
- Size of remote file:
- 438 MB
- SHA256:
- 31a005e772acf063f37278ec24a00603b5226f612b21a50bf912b5e3f3c8fb1f
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