Instructions to use Jeevesh8/init_bert_ft_qqp-90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-90 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-90")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-90") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-90") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14719133798dcf29903defc67b54b85791b48e1778e81f79a3e3a4e02679931f
- Size of remote file:
- 438 MB
- SHA256:
- 00a51c7e9f8f321e165733214f285e6af8a99e64b143fd0260cb82d540436a78
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