import pandas as pd import gradio as gr import pyterrier as pt pt.init() from pyterrier_gradio import Demo, MarkdownFile, interface, df2code, code2md, EX_R from pyterrier_t5 import MonoT5ReRanker model = MonoT5ReRanker() COLAB_NAME = 'pyterrier_t5.ipynb' COLAB_INSTALL = ''' !pip install -q git+https://github.com/terrier-org/pyterrier_t5 '''.strip() def predict(input): code = f'''import pandas as pd import pyterrier as pt ; pt.init() from pyterrier_t5 import MonoT5ReRanker model = MonoT5ReRanker() model({df2code(input)}) ''' res = model(input) res['score'] = res['score'].map(lambda x: round(x, 4)) res = res.sort_values(['qid', 'rank']) return (res, code2md(code, COLAB_INSTALL, COLAB_NAME, colab=False)) interface( MarkdownFile('README.md'), Demo( predict, EX_R, [] ), MarkdownFile('wrapup.md'), ).launch(share=False)