| | --- |
| | license: apache-2.0 |
| | datasets: |
| | - wikisql |
| | language: |
| | - en |
| | pipeline_tag: text2text-generation |
| | tags: |
| | - nl2sql |
| | widget: |
| | - text: "question: get people name with age less 25 table: id, name, age" |
| | example_title: "less than" |
| | - text: "question: get people name with age equal 25 table: id, name, age" |
| | example_title: "equal" |
| | --- |
| | |
| | new version: [LarkAI/codet5p-770m_nl2sql_oig](https://huggingface.co/LarkAI/codet5p-770m_nl2sql_oig) |
| |
|
| | use oig-sql dataset and support more complex sql parse |
| |
|
| | # How to Use |
| |
|
| | ```python |
| | import torch |
| | from transformers import AutoTokenizer, BartForConditionalGeneration |
| | |
| | device = torch.device('cuda:0') |
| | |
| | tokenizer = AutoTokenizer.from_pretrained("LarkAI/bart_large_nl2sql") |
| | model = BartForConditionalGeneration.from_pretrained("LarkAI/bart_large_nl2sql").to(device) |
| | |
| | text = "question: get people name with age less 25 table: id, name, age" |
| | inputs = tokenizer([text], max_length=1024, return_tensors="pt") |
| | output_ids = model.generate(inputs["input_ids"].to(device), num_beams=self.beams, max_length=128, min_length=8) |
| | response_text = tokenizer.batch_decode(output_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] |
| | # SELECT name FROM table WHERE age < 25 |
| | ``` |
| |
|
| | reference: [juierror/flan-t5-text2sql-with-schema](https://huggingface.co/juierror/flan-t5-text2sql-with-schema) - fix this [discussion](https://huggingface.co/juierror/flan-t5-text2sql-with-schema/discussions/5) |
| |
|
| | # How to Train |
| |
|
| | Quick start: https://github.com/huggingface/transformers/blob/main/examples/pytorch/summarization/README.md |
