Instructions to use MrezaPRZ/sql-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MrezaPRZ/sql-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MrezaPRZ/sql-encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MrezaPRZ/sql-encoder") model = AutoModelForSequenceClassification.from_pretrained("MrezaPRZ/sql-encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2de34d7a0e3fc469da6ada13410afcc21858d715cea4331d9cd28ae4e326f776
- Size of remote file:
- 2.56 GB
- SHA256:
- e1d94d7682fc29e4eb9776088bf3407ff250a853313a752dd0bc1fbd47a4360d
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