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import gradio as gr
from fine_tuner import fine_tune_model
from model_selector import get_model_list
from utils import load_dataset
def train_model(dataset_url, model_name, epochs, batch_size, learning_rate):
dataset = load_dataset(dataset_url)
metrics = fine_tune_model(dataset, model_name, epochs, batch_size, learning_rate)
return metrics
def main():
model_options = get_model_list()
interface = gr.Interface(
fn=train_model,
inputs=[
gr.inputs.Textbox(label="Dataset URL"),
gr.inputs.Dropdown(choices=model_options, label="Select Model"),
gr.inputs.Slider(minimum=1, maximum=10, default=3, label="Epochs"),
gr.inputs.Slider(minimum=1, maximum=64, default=16, label="Batch Size"),
gr.inputs.Slider(minimum=1e-5, maximum=1e-1, step=1e-5, default=1e-4, label="Learning Rate")
],
outputs="json",
title="Transformers Fine Tuner",
description="Fine-tune pre-trained transformer models on custom datasets."
)
interface.launch()
if __name__ == "__main__":
main()
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