Vigen1/text2sql

1import gradio as gr2from transformers import AutoModelForSeq2SeqLM, AutoTokenizer3 4 5def get_output(question, context):6    model_name = 't5-small'7    8    tokenizer = AutoTokenizer.from_pretrained(model_name)9    10    finetuned_model = AutoModelForSeq2SeqLM.from_pretrained("finetuned_model_2_epoch")11    12    prompt = f"""Tables:13    {context}14    15    Question:16    {question}17    18    Answer:19    """20    21    inputs = tokenizer(prompt, return_tensors='pt')22    23    output = tokenizer.decode(24        finetuned_model.generate(25            inputs["input_ids"],26            max_new_tokens=200,27        )[0],28        skip_special_tokens=True29    )30    31    return output32 33interface = gr.Interface(fn=get_output, inputs = ["text", "text"], outputs=["text"])34interface.launch()