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--- |
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language: en |
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datasets: |
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- wikisql |
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widget: |
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- text: 'question: get people name with age equal 25 table: id, name, age' |
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--- |
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# How to use |
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```python |
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from typing import List |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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tokenizer = AutoTokenizer.from_pretrained("juierror/flan-t5-text2sql-with-schema") |
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model = AutoModelForSeq2SeqLM.from_pretrained("juierror/flan-t5-text2sql-with-schema") |
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def prepare_input(question: str, table: List[str]): |
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table_prefix = "table:" |
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question_prefix = "question:" |
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join_table = ",".join(table) |
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inputs = f"{question_prefix} {question} {table_prefix} {join_table}" |
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input_ids = tokenizer(inputs, max_length=512, return_tensors="pt").input_ids |
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return input_ids |
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def inference(question: str, table: List[str]) -> str: |
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input_data = prepare_input(question=question, table=table) |
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input_data = input_data.to(model.device) |
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outputs = model.generate(inputs=input_data, num_beams=10, top_k=10, max_length=700) |
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result = tokenizer.decode(token_ids=outputs[0], skip_special_tokens=True) |
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return result |
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print(inference(question="get people name with age equal 25", table=["id", "name", "age"])) |
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``` |