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lt2t_content_selection
kategaranina/lt2t_content_selection
lt2t_content_selection is a machine learning model from kategaranina. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
This is a fine-tuned t5-base model for generating logical form templates from table metadata. It is a part of table-to-text pipeline with content selection and logical reasoning, trained on Logic2Text dataset. The las…
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At a glance
- Library
- transformers
- License
- mit
- Model type
- t5
- Access
- Public
- Created
- Jan 7, 2024
- Updated
- Jan 10, 2024
- SHA
- 9431f584
Datasets
Model card
From the Hugging Face model README
Model description
This is a fine-tuned t5-base model for generating logical form templates from table metadata. It is a part of table-to-text pipeline with content selection and logical reasoning, trained on Logic2Text dataset. The last pipeline step is done by kategaranina/lt2t_lf_to_text model. For relevant code, see LT2T repository on GitHub.
Example of input:
Title: wake forest demon deacons football , 1980 - 89.
Column date. Type: date. Stats: Column has all unique values, all values have one occurrence,
first: 1987-09-12, last: 1987-11-21, max diff days: 70, max diff months: 2, max diff years: 0.
Value: 09 / 12 / 1987.
...
Column location. Type: str. Stats: Column has most unique values, one value has most occurrences,
most values have one occurrence. Value: groves stadium winston - salem , nc.
...
Example of output:
round_eq { avg { all_rows ; attendance } ; X }
- Library
- transformers
- Type
- t5
- License
- mit
- Languages
- en
- Created
- Jan 7, 2024
- Updated
- Jan 10, 2024