Instructions to use Jeevesh8/init_bert_ft_qqp-25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-25 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-25")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-25") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-25") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87d04cf789197318a69dba542b0295fca6086c75d9de7fb544856a6403a984d8
- Size of remote file:
- 438 MB
- SHA256:
- a45310dc6c1fb131aedefa8da43b1c41eab0642f6bc44377b3bded4c089982c3
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