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import os | |
import gradio as gr | |
from transformers import pipeline | |
sd_description = "ζεηζεΎη" | |
sd_examples = [["ε°η«"], ["cat"], ["dog"]] | |
sd_demo = gr.Interface.load("models/runwayml/stable-diffusion-v1-5", title='ζεηζεΎη', 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='εΎηθ―ε«') | |
pipe = pipeline("dreamlike-art/dreamlike-photoreal-2.0") | |
examples = [["θ½ζ₯"], ["ζ²ζ»©"]] | |
app_v1 = gr.Interface.from_pipeline(pipe, examples=examples, title='εΎηηζ') | |
demo = gr.TabbedInterface([sd_demo, app, app_v1], ["ζεηζεΎη", "εΎηθ―ε«", "ζεηζεΎηv1"]) | |
demo.launch() | |