Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use hiwensen/bert_sql_classfication with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hiwensen/bert_sql_classfication with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hiwensen/bert_sql_classfication")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hiwensen/bert_sql_classfication") model = AutoModelForSequenceClassification.from_pretrained("hiwensen/bert_sql_classfication") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37024e8497c7b6bfebb6cd7e99f4e251187dbf82e0f955a6eb1fee6d8671cd23
- Size of remote file:
- 268 MB
- SHA256:
- 394179cd1421c770d95fd5e4a12f5fd86cc06bc727737d6bec96582438c43928
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