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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«')
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 = [["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()
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