Instructions to use flagship/sqlclassification_normal_bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flagship/sqlclassification_normal_bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="flagship/sqlclassification_normal_bert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("flagship/sqlclassification_normal_bert_model") model = AutoModelForSequenceClassification.from_pretrained("flagship/sqlclassification_normal_bert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa454e4e0fd3e9f5fcb882e8725976a74217f00f04bc2b28eb435aced4dd1a1b
- Size of remote file:
- 438 MB
- SHA256:
- f9debcd7f956e38803f2c51613196bf2e3efa8fe8cb58b4653631af1ab755e66
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