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import gradio as gr
theme = gr.themes.Soft()
query_examples=[
("Default Option 1"),
("Default Option 2"),
("Default Option 3")
]
# Define a function that echoes the input text
def echo_text(input_text):
return input_text
with gr.Interface(
fn=echo_text,
inputs=gr.Textbox(placeholder="Enter text here..."),
outputs=gr.Textbox(),
examples=query_examples,
live=True,
title="LLM Evaluator with Linguistic Scrutiny",
theme=theme
) as iface:
blocks = gr.Blocks()
with gr.Row():
vicuna_model_selector = gr.Dropdown(["7b", "13b", "33b"], label="Vicuna Model", placeholder="Select model size")
llama_model_selector = gr.Dropdown(["7B", "13B", "30B", "65B"], label="LLaMa Model", placeholder="Select model size")
chatgpt_api_key = gr.Textbox(label="ChatGPT API Key", type="password", placeholder="Enter your API key")
# Strategy 1 - QA-Based Prompting
with gr.Accordion("Strategy 1 - QA-Based Prompting", style="font-weight: bold; font-size: 16px;"):
with gr.Row():
chatgpt_btn = gr.Button("ChatGPT")
llama_btn = gr.Button("LLaMA")
vicuna_btn = gr.Button("Vicuna")
alpaca_btn = gr.Button("Alpaca")
flant5_btn = gr.Button("Flan-T5")
# Strategy 2 - Instruction-Based Prompting
with gr.Accordion("Strategy 2 - Instruction-Based Prompting", style="font-weight: bold; font-size: 16px;"):
with gr.Row():
chatgpt_btn = gr.Button("ChatGPT")
llama_btn = gr.Button("LLaMA")
vicuna_btn = gr.Button("Vicuna")
alpaca_btn = gr.Button("Alpaca")
flant5_btn = gr.Button("Flan-T5")
# Strategy 3 - Structured Prompting
with gr.Accordion("Strategy 3 - Structured Prompting", style="font-weight: bold; font-size: 16px;"):
with gr.Row():
chatgpt_btn = gr.Button("ChatGPT")
llama_btn = gr.Button("LLaMA")
vicuna_btn = gr.Button("Vicuna")
alpaca_btn = gr.Button("Alpaca")
flant5_btn = gr.Button("Flan-T5")
iface.launch()
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