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import gradio as gr | |
import torch | |
from duffusers import StableDiffusers3Pipeline | |
def image_generation(prompt): | |
device = "cuda" if torch.cuda.is_available() else "cpu" | |
pipeline = StableDiffusers3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", | |
torch_dtype=torch.float16 if device == "cuda" else torch.float32, | |
text_encoder_3 = None, | |
tokenizer_3 = None) | |
# pipeline.to(device) | |
pipeline.enable_model_cpu_offload() | |
image = pipeline( | |
prompt = prompt, | |
negative_prompt = "blurred, ugly, watermark, low resolution, blurry, nude", | |
num_inference_steps = 40, | |
height=1024, | |
width=1024, | |
guidance_scale=8.0 | |
).images[0] | |
image.show() | |
interface= gr.interface( | |
fn=image_generation, | |
inputs = gr.Textbox(lines="2", placeholder="Enter Your Prompt ..."), | |
outputs = gr.Image(type="pil"), | |
title = "AI Text Generation By SD-3M", | |
examples = "A magician cat doing spell" | |
) | |
interface.launch() |