gradio_demo / app.py
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import os
import gradio as gr
from transformers import pipeline
sd_description = "ζ–‡ε­—η”Ÿζˆε›Ύη‰‡"
sd_examples = [["小猫"], ["cat"], ["dog"]]
sd_demo = gr.Interface.load("models/runwayml/stable-diffusion-v1-5", title='ζ–‡ε­—η”Ÿζˆε›Ύη‰‡', examples=sd_examples)
pipe = pipeline("image-classification")
examples = [[os.path.join(os.path.dirname(__file__), "lion.jpg")], [os.path.join(os.path.dirname(__file__), "cat.jpeg")]]
app = gr.Interface.from_pipeline(pipe, examples=examples, title='ε›Ύη‰‡θ―†εˆ«')
from diffusers import StableDiffusionPipeline
import torch
model_id = "dreamlike-art/dreamlike-photoreal-2.0"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
examples = [["落ζ—₯"], ["ζ²™ζ»©"]]
app_v1 = gr.Interface.from_pipeline(pipe, examples=examples, title='ε›Ύη‰‡η”Ÿζˆ')
demo = gr.TabbedInterface([sd_demo, app, app_v1], ["ζ–‡ε­—η”Ÿζˆε›Ύη‰‡", "ε›Ύη‰‡θ―†εˆ«", "ζ–‡ε­—η”Ÿζˆε›Ύη‰‡v1"])
demo.launch()