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| import numpy as np | |
| import requests | |
| import streamlit as st | |
| #def main(): | |
| st.title("Scientific Question Generation") | |
| checkpoints = ['dhmeltzer/bart-large_askscience-qg', | |
| 'dhmeltzer/flan-t5-base_askscience-qg', | |
| 'google/flan-t5-xxl'] | |
| headers = {"Authorization": f"Bearer {st.secrets['HF_token']}"} | |
| def query(checkpoint, payload): | |
| API_URL = f"https://api-inference.huggingface.co/models/{checkpoint}" | |
| response = requests.post(API_URL, | |
| headers=headers, | |
| json=payload) | |
| return response.json() | |
| # User search | |
| user_input = st.text_area("Question Generator", | |
| """Black holes are the most gravitationally dense objects in the universe.""") | |
| # Filters | |
| st.sidebar.markdown("**Filters**") | |
| temperature = st.sidebar.slider("Temperature", 0.0, 1.0, 0.0,.1) | |
| if user_input: | |
| for checkpoint in checkpoints: | |
| output = query(checkpoint,{ | |
| "inputs": user_input, | |
| "temperature":temperature, | |
| "wait_for_model":True}) | |
| model_name = checkpoint.split('/')[1] | |
| st.write(f'Model {model_name}: {output}') | |
| #if __name__ == "__main__": | |
| # main() | |