Instructions to use Jeevesh8/init_bert_ft_qqp-61 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-61 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-61")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-61") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-61") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5dadd74d20dab73025add9547f7364eabf23a3b821ce6d04827e0c88e4cb618
- Size of remote file:
- 438 MB
- SHA256:
- 5047c3ecd80071609d554f8665aa79015aa7d710fbf2a732efb9449f207dc3ac
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