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import os
os.system("pip install gradio diffusers torch transformers")
import gradio as gr
from diffusers import StableDiffusionXLPipeline
import torch
pipe = StableDiffusionXLPipeline.from_pretrained(
"segmind/SSD-1B",
torch_dtype=torch.float16,
use_safetensors=True,
variant="fp16"
)
pipe.to("cuda")
def generate_image(prompt, neg_prompt):
image = pipe(
prompt=prompt,
negative_prompt=neg_prompt
).images[0]
return image
prompt = gr.Text(
label="Prompt",
show_label=False,
max_lines=1,
placeholder="Enter your prompt",
container=False,
)
neg_prompt = gr.Text(
label="Negative Prompt",
show_label=False,
max_lines=1,
placeholder="Enter your negative prompt",
container=False,
)
iface = gr.Interface(
fn=generate_image,
inputs=[prompt, neg_prompt],
outputs="image",
title="Text to Image Generation",
examples=[
["a painting of a cute cat sitting on a chair", "ugly, blurry"],
["an astronaut riding a horse on mars", "poorly drawn"]
],
allow_flagging=False
)
iface.launch(share=True) |