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widget: - text: "Is this review positive or negative? Review: Best cast iron skillet you will ever buy." example_title: "Sentiment analysis" - text: "Barack Obama nominated Hilary Clinton as his secretary of state on Monday. He chose her because she had ..." example_title: "Coreference resolution" - text: "On a shelf, there are five books: a gray book, a red book, a purple book, a blue book, and a black book ..." example_title: "Logic puzzles" - text: "The two men running to become New York City's next mayor will face off in their first debate Wednesday night ..." example_title: "Reading comprehension"
Model Card for Model ID
Generate SQL from Natural Language question with a SQL context.
Model Details
Model Description
BART from facebook/bart-large-cnn is fintuned on gretelai/synthetic_text_to_sql dataset to generate SQL from NL and SQL context
- Model type: [BART]
- Language(s) (NLP): English
- License: openrail
- Finetuned from model facebook/bart-large-cnn
- Dataset: gretelai/synthetic_text_to_sql
Uses
Direct Use
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Downstream Use [optional]
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How to Get Started with the Model
Use the code below to get started with the model.
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Training Details
Training Data
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Training Procedure
Preprocessing [optional]
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Training Hyperparameters
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Speeds, Sizes, Times [optional]
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Evaluation
Testing Data, Factors & Metrics
Testing Data
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Factors
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Metrics
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Results
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Technical Specifications [optional]
Model Architecture and Objective
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Compute Infrastructure
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Citation
BibTeX:
@software{gretel-synthetic-text-to-sql-2024, author = {Meyer, Yev and Emadi, Marjan and Nathawani, Dhruv and Ramaswamy, Lipika and Boyd, Kendrick and Van Segbroeck, Maarten and Grossman, Matthew and Mlocek, Piotr and Newberry, Drew}, title = {{Synthetic-Text-To-SQL}: A synthetic dataset for training language models to generate SQL queries from natural language prompts}, month = {April}, year = {2024}, url = {https://huggingface.co/datasets/gretelai/synthetic-text-to-sql} }
@article{DBLP:journals/corr/abs-1910-13461, author = {Mike Lewis and Yinhan Liu and Naman Goyal and Marjan Ghazvininejad and Abdelrahman Mohamed and Omer Levy and Veselin Stoyanov and Luke Zettlemoyer}, title = {{BART:} Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension}, journal = {CoRR}, volume = {abs/1910.13461}, year = {2019}, url = {http://arxiv.org/abs/1910.13461}, eprinttype = {arXiv}, eprint = {1910.13461}, timestamp = {Thu, 31 Oct 2019 14:02:26 +0100}, biburl = {https://dblp.org/rec/journals/corr/abs-1910-13461.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
Model Card Authors [optional]
[Swastik Maiti]