Instructions to use JiZha/text2sql_schema_item_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JiZha/text2sql_schema_item_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JiZha/text2sql_schema_item_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("JiZha/text2sql_schema_item_classifier") model = AutoModelForMaskedLM.from_pretrained("JiZha/text2sql_schema_item_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f2879512b0bea2ab0d4c411ef1b7ad59ba9411cab2194a2764a133d5ccce0ec
- Size of remote file:
- 1.55 GB
- SHA256:
- 8bf346bd3d35d552d0c4e0170b6014799aa4d391ee614a0bd6cd9bb27cb89348
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