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import gradio as gr
import os
from transformers import pipeline
title = "📗Health and Mindful Story Gen❤️"
# Define the examples to show in the interface
examples = [
["Mental Body Scan"],
["Stretch, Calm, Breath"],
["Relaxed Seat Breath"],
["Walk Feel"],
["Brain gamification"],
["Alleviating stress"],
["Helping breathing, satisfaction"],
["Relieve Stress, Build Support"],
["Relaxation Response"],
["Deep Breaths"],
["Delete Not Helpful Thoughts"],
["Strengthen Helpful"],
["Reprogram Pain Stress Reactions"],
["Sleep Better and Find Joy"],
["Yoga Sleep"],
["Being a Happier and Healthier Person"],
["Relieve Pain"],
["Learn to Use Mindfulness to Affect Well Being"],
["Build and Boost Mental Strength"],
["Spending Time Outdoors"],
["Daily Routine Tasks"],
["Eating and Drinking - Find Healthy Nutrition Habits"],
["Drinking - Find Reasons and Cut Back or Quit Entirely"],
["Feel better each day when you awake by"],
["Feel better physically by"],
["Practicing mindfulness each day"],
["Be happier by"],
["Meditation can improve health"],
["Spending time outdoors"],
["Stress is relieved by quieting your mind, getting exercise and time with nature"],
["Break the cycle of stress and anxiety"],
["Feel calm in stressful situations"],
["Deal with work pressure"],
["Learn to reduce feelings of overwhelmed"]
]
# Initialize the models using Hugging Face pipelines
generator1 = pipeline("text-generation", model="gpt2-large")
generator2 = pipeline("text-generation", model="EleutherAI/gpt-neo-2.7B")
generator3 = pipeline("text-generation", model="EleutherAI/gpt-j-6B")
with gr.Blocks() as demo:
gr.Markdown(f"# {title}")
input_textbox = gr.Textbox(lines=5, label="Enter a sentence to get another sentence.")
with gr.Row():
gen1_output = gr.Textbox(label="GPT-2 Large Output")
gen2_output = gr.Textbox(label="GPT-Neo Output")
gen3_output = gr.Textbox(label="GPT-J Output")
def generate_outputs(input_text):
out1 = generator1(input_text, max_length=50)[0]['generated_text']
out2 = generator2(input_text, max_length=50)[0]['generated_text']
out3 = generator3(input_text, max_length=50)[0]['generated_text']
return out1, out2, out3
gr.Button("Generate").click(
fn=generate_outputs,
inputs=input_textbox,
outputs=[gen1_output, gen2_output, gen3_output]
)
gr.Examples(examples=examples, inputs=input_textbox, examples_per_page=100)
demo.launch(share=False)
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