Instructions to use strongpear/BERT_query_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use strongpear/BERT_query_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="strongpear/BERT_query_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("strongpear/BERT_query_classifier") model = AutoModelForSequenceClassification.from_pretrained("strongpear/BERT_query_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b4fa75aecf8c23e7afc737f512b432fda9b4da53467f7b1f105cf631ea7dba5
- Size of remote file:
- 535 MB
- SHA256:
- f5ff5c2a091f7e39d2a3e34f7623dc2547b62b9c104b5e6e618260cffb1173eb
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