30 lines
856 B
Python
30 lines
856 B
Python
import gradio as gr
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import torch
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import gc
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from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
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import os
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os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "max_split_size_mb:32"
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model_id = "stabilityai/stable-diffusion-2-1"
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
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pipe = pipe.to("cuda")
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def text2image(prompt):
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image = pipe(prompt).images[0]
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return image
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demo = gr.Interface(fn=text2image,
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inputs='text',
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outputs='image',
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title = "text2image",
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examples = ['a photo of an astronaut riding a horse on mars'])
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if __name__ == "__main__":
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demo.queue(concurrency_count=3).launch(server_name = "0.0.0.0", server_port = 7013)
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