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import torch
import gradio as gr
from gradio import processing_utils, utils
from PIL import Image
import random
from diffusers import (
DiffusionPipeline,
AutoencoderKL,
StableDiffusionControlNetPipeline,
ControlNetModel,
StableDiffusionLatentUpscalePipeline,
StableDiffusionImg2ImgPipeline,
StableDiffusionControlNetImg2ImgPipeline,
DPMSolverMultistepScheduler, # <-- Added import
EulerDiscreteScheduler # <-- Added import
)
print(f"Is CUDA available: {torch.cuda.is_available()}")
print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
import time
from style import css
BASE_MODEL = "SG161222/Realistic_Vision_V5.1_noVAE"
title = "Flan T5 and Vanilla T5"
description = "This demo compares [T5-large](https://huggingface.co/t5-large) and [Flan-T5-XX-large](https://huggingface.co/google/flan-t5-xxl). Note that T5 expects a very specific format of the prompts, so the examples below are not necessarily the best prompts to compare."
def inference(text):
output_flan = ""
output_vanilla = ""
return [output_flan, output_vanilla]
io = gr.Interface(
inference,
gr.Textbox(lines=3),
outputs=[
gr.Textbox(lines=3, label="Flan T5"),
gr.Textbox(lines=3, label="T5")
],
title=title,
description=description,
)
io.launch() |