Instructions to use flagship/sqlclassification_normal_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flagship/sqlclassification_normal_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="flagship/sqlclassification_normal_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("flagship/sqlclassification_normal_bert") model = AutoModelForSequenceClassification.from_pretrained("flagship/sqlclassification_normal_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20877904f58df8aa4ad5a45e7cac86f30b8aa7e69a9488cd0c72fdfc2ad1174e
- Size of remote file:
- 438 MB
- SHA256:
- 201dc65e10db137c8d92f6f0c8ef8f2392140ce25766f9dda61250932bedb180
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