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| ##################################### Imports ###################################### | |
| # Generic imports | |
| import gradio as gr | |
| # Module imports | |
| from utilities.setup import get_json_cfg | |
| from utilities.templates import prompt_template | |
| ########################### Global objects and functions ########################### | |
| conf = get_json_cfg() | |
| def textbox_visibility(radio): | |
| value = radio | |
| if value == "Hugging Face Hub Dataset": | |
| return gr.Dropdown(visible=bool(1)) | |
| else: | |
| return gr.Dropdown(visible=bool(0)) | |
| def upload_visibility(radio): | |
| value = radio | |
| if value == "Upload Your Own": | |
| return gr.UploadButton(visible=bool(1)) #make it visible | |
| else: | |
| return gr.UploadButton(visible=bool(0)) | |
| def greet(model_name, inject_prompt, dataset): | |
| """The model call""" | |
| return f"Hello!! Using model: {model_name} with template: {inject_prompt}" | |
| ##################################### App UI ####################################### | |
| def main(): | |
| with gr.Blocks() as demo: | |
| ##### Title Block ##### | |
| gr.Markdown("# Instruction Tuning with Unsloth") | |
| ##### Model Inputs ##### | |
| # Select Model | |
| modelnames = conf['model']['choices'] | |
| model_name = gr.Dropdown(label="Supported Models", | |
| choices=modelnames, | |
| value=modelnames[0]) | |
| # Prompt template | |
| inject_prompt = gr.Textbox(label="Prompt Template", | |
| value=prompt_template()) | |
| # Dataset choice | |
| dataset_choice = gr.Radio(label="Choose Dataset", | |
| choices=["Hugging Face Hub Dataset", "Upload Your Own"], | |
| value="Hugging Face Hub Dataset") | |
| dataset_predefined = gr.Textbox(label="Hugging Face Hub Dataset", | |
| value='yahma/alpaca-cleaned', | |
| visible=True) | |
| dataset_upload = gr.UploadButton(label="Upload Dataset (csv, jsonl, or txt)", | |
| file_types=[".csv",".jsonl", ".txt"], | |
| visible=False) | |
| dataset_choice.change(textbox_visibility, | |
| dataset_choice, | |
| dataset_predefined) | |
| dataset_choice.change(upload_visibility, | |
| dataset_choice, | |
| dataset_upload) | |
| # Hyperparameters (allow selection, but hide in accordion.) | |
| with gr.Accordion("Advanced Tuning", open=False): | |
| # config | |
| peftparams = conf['model']['peft'] | |
| sftparams = conf['model']['sft'] | |
| # accordion container content | |
| gr.Markdown("### PEFT Parameters") | |
| r = gr.Textbox(label="r", value=peftparams['r']) | |
| alpha = gr.Textbox(label="LoRA alpha", value=peftparams['alpha']) | |
| dropout = gr.Textbox(label="LoRA dropout", value=peftparams['dropout']) | |
| bias = gr.Textbox(label="Bias", value=peftparams['bias']) | |
| seed = gr.Textbox(label="Random State", value=peftparams['seed']) | |
| rslora = gr.Textbox(label="Use R-S LoRA", value=peftparams['rslora']) | |
| pefts = [r, alpha, dropout, bias, seed, rslora] | |
| gr.Markdown("List of items") | |
| gr.Markdown("### Supervised Fine-Tuning Parameters") | |
| gr.Markdown("List of items") | |
| ##### Execution ##### | |
| # Setup button | |
| tune_btn = gr.Button("Start Fine Tuning") | |
| # Text output (for now) | |
| output = gr.Textbox(label="Output") | |
| # Execute button | |
| tune_btn.click(fn=greet, | |
| inputs=[model_name, inject_prompt, dataset_predefined], | |
| outputs=output) | |
| # Launch baby | |
| demo.launch() | |
| ##################################### Launch ####################################### | |
| if __name__ == "__main__": | |
| main() |