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| import gradio as gr | |
| from scripts.bold import generate_and_evaluate_causal_lm_toxicity_bold | |
| from scipy.stats import anderson_ksamp | |
| def run_evaluation(model_id): | |
| outputs = generate_and_evaluate_causal_lm_toxicity_bold(model_id, './prompts') | |
| pvals = {k: anderson_ksamp(list(outputs[k]['raw'].values())).significance_level for k in outputs.keys()} | |
| return outputs, pvals | |
| demo = gr.Blocks() | |
| with demo: | |
| model_id = gr.Text() | |
| button = gr.Button("Run Evaluation") | |
| raw_outputs = gr.Json(label="Evaluation Results") | |
| pvalues = gr.Json(label="P-values") | |
| gr.Examples( | |
| examples=[["EleutherAI/gpt-neo-125M"]], | |
| fn=run_evaluation, | |
| inputs=[model_id], | |
| outputs=[pvalues], | |
| ) | |
| button.click( | |
| fn=run_evaluation, | |
| inputs=[model_id], | |
| outputs=[raw_outputs, pvalues] | |
| ) | |
| demo.launch() | |