ellenhp/query2osm

1from gradio.components import Component2import torch3from hydra import Hydra4from transformers import AutoTokenizer5import gradio as gr6from hydra import Hydra7import os8from typing import Any, Optional9 10model_name = "ellenhp/query2osm-bert-v1"11tokenizer = AutoTokenizer.from_pretrained(model_name, padding=True)12model = Hydra.from_pretrained(model_name).to('cpu')13 14def predict(input_query):15    with torch.no_grad():16        print(input_query)17        input_text = input_query.strip().lower()18        inputs = tokenizer(input_text, return_tensors="pt")19        outputs = model.forward(inputs.input_ids)20        return {classification[0]: classification[1] for classification in outputs.classifications[0]}21 22 23textbox = gr.Textbox(label="Query",24                     placeholder="Quick bite to eat near me")25label = gr.Label(label="Result", num_top_classes=5)26 27gradio_app = gr.Interface(28    predict,29    inputs=[textbox],30    outputs=[label],31    title="Query Classification",32)33 34if __name__ == "__main__":35    gradio_app.launch()36