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# pip install transformers gradio scipy ftfy "ipywidgets>=7,<8" datasets diffusers
import gradio as gr
import torch
from torch import autocast
from diffusers import StableDiffusionPipeline
model_id = "hakurei/waifu-diffusion"
device = "cpu"
# pipe = StableDiffusionPipeline.from_pretrained(model_id,
# resume_download=True, # 模型文件断点续传
# torch_dtype=torch.float16,
# revision='fp16')
# pipe = pipe.to(device)
block = gr.Blocks(css=".container { max-width: 800px; margin: auto; }")
num_samples = 2
def infer(prompt):
print(prompt)
return prompt
# with autocast("cuda"):
# images = pipe([prompt] * num_samples,
# hight=111,
# width=100,
#
# guidance_scale=7.5)["sample"]
# return images
with block as demo:
gr.Markdown("<h1><center>Waifu Diffusion</center></h1>")
gr.Markdown(
"waifu-diffusion is a latent text-to-image diffusion model that has been conditioned on high-quality anime images through fine-tuning."
)
with gr.Group():
with gr.Box():
with gr.Column().style(mobile_collapse=False, equal_height=True):
text = gr.Textbox(
label="Enter your prompt",
show_label=False,
max_lines=1
).style(
border=(True, False, True, True),
rounded=(True, False, False, True),
container=False,
)
slider = gr.Slider(0, 1000, 10)
btn = gr.Button("Run").style(
margin=False,
rounded=(False, True, True, False),
)
gallery = gr.Gallery(
label="Generated images",
show_label=False
).style(
grid=[2],
height="auto"
)
gr.Interface
text.submit(infer,
inputs=[text,slider] ,
outputs=gallery)
btn.click(infer, inputs=[text], outputs=gallery)
gr.Markdown(
"""___
<p style='text-align: center
'>
Created by https://huggingface.co/hakurei
<br/>
</p>"""
)
demo.launch(debug=True)
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