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import gradio as gr
import subprocess
# Function to execute hf_merge.py with provided parameters
def run_hf_merge(repo_list, output_dir, staging='./staging', p=0.5, lambda_val=1.0, dry_run=False):
command = [
"python3", "hf_merge.py", repo_list, output_dir,
"-staging", staging, "-p", str(p), "-lambda", str(lambda_val)
]
if dry_run:
command.append("--dry")
result = subprocess.run(command, capture_output=True, text=True)
if result.returncode == 0:
return "Merge completed successfully.\n" + result.stdout
else:
return "Error during merge.\n" + result.stderr
# Gradio interface
interface = gr.Interface(
fn=run_hf_merge,
inputs=[
gr.Textbox(label="Repo List File"),
gr.Textbox(label="Output Directory"),
gr.Textbox(label="Staging Directory", value="./staging"),
gr.Number(label="Dropout Probability", value=0.5),
gr.Number(label="Scaling Factor", value=1.0),
gr.Checkbox(label="Dry Run")
],
outputs="text",
title="HuggingFace Model Merger",
description="Merge HuggingFace models using the technique described in 'Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch'."
)
if __name__ == "__main__":
interface.launch() |