Instructions to use Jeevesh8/init_bert_ft_qqp-80 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-80 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-80")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-80") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-80") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8df34d0fb8ceeee7937b3aa04a4ad16cd5f33fea9851c59717914317a4384dc
- Size of remote file:
- 438 MB
- SHA256:
- 46e0b33d96f0211a68a007c34eb12c4eb9875122b542155af7f95d95b2588acc
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