Spaces:
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import gradio as gr | |
from transformers import pipeline | |
# Install required packages | |
import os | |
os.system("pip install -r requirements.txt") | |
# Load the pipeline for text generation | |
pipe = pipeline( | |
"text-generation", | |
model="Ar4ikov/gpt2-650k-stable-diffusion-prompt-generator", | |
tokenizer="gpt2" | |
) | |
# Function to generate text based on input prompt | |
def generate_text(prompt): | |
return pipe(prompt, max_length=77)[0]["generated_text"] | |
# Create a Gradio interface | |
iface = gr.Interface( | |
fn=generate_text, | |
inputs=gr.Textbox(lines=5, label="Prompt"), | |
outputs=gr.Textbox(label="Output", show_copy_button=True), | |
title="AI Art Prompt Generator", | |
description="Art Prompt Generator is a user-friendly interface designed to optimize input for AI Art Generator or Creator. For faster generation speeds, it's recommended to load the model locally with GPUs, as the online demo at Hugging Face Spaces utilizes CPU, resulting in slower processing times.", | |
api_name="predict" | |
) | |
# Integrate external CSS | |
iface.stylesheets.append("styles.css") | |
# Launch the interface | |
iface.launch(show_api=True) |