readme: ---
  language: en
  datasets:
  - wikisql
  widget:
  - text: "question: get people name with age equal 25 table: id, name, age"
  ---
  
  # How to use
  ```python
  from typing import List
  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
  
  tokenizer = AutoTokenizer.from_pretrained("juierror/text-to-sql-with-table-schema")
  model = AutoModelForSeq2SeqLM.from_pretrained("juierror/text-to-sql-with-table-schema")
  
  def prepare_input(question: str, table: List[str]):
      table_prefix = "table:"
      question_prefix = "question:"
      join_table = ",".join(table)
      inputs = f"{question_prefix} {question} {table_prefix} {join_table}"
      input_ids = tokenizer(inputs, max_length=700, return_tensors="pt").input_ids
      return input_ids
  
  def inference(question: str, table: List[str]) -> str:
      input_data = prepare_input(question=question, table=table)
      input_data = input_data.to(model.device)
      outputs = model.generate(inputs=input_data, num_beams=10, top_k=10, max_length=700)
      result = tokenizer.decode(token_ids=outputs[0], skip_special_tokens=True)
      return result
  
  print(inference(question="get people name with age equal 25", table=["id", "name", "age"]))
  ```
  
  There are newer version of this using Flan-T5 as a based model. You can check out [here](https://huggingface.co/juierror/flan-t5-text2sql-with-schema)