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| from diffusers import StableDiffusionPipeline | |
| import torch | |
| from uuid import uuid4 | |
| from PIL import Image | |
| import gradio as gr | |
| model_path = "sd-pokemon-model" | |
| pipe = StableDiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float16, low_cpu_mem_usage=False, device_map=None) | |
| # pipe.to("cuda") | |
| def predict(prompt): | |
| image = pipe(prompt=prompt).images[0] | |
| tmp_filename = f"/tmp/{uuid4()}.png" | |
| image.save(tmp_filename) | |
| img = Image.open(tmp_filename) | |
| return img | |
| title = "Stable Diffusion Pokemon Generator" | |
| description = "Generate Pokemon from text prompts using Stable Diffusion v1.4" | |
| article="<p style='text-align: center'><a href='https://github.com/hoangkimthuc/diffusers' target='_blank'>Click here to see the original repo of this app</a></p>" | |
| examples = ["yoda", "pikachu", "charmander"] | |
| interpretation='default' | |
| enable_queue=True | |
| text_to_image_app = gr.Interface(fn=predict, | |
| inputs="text", | |
| outputs="image", | |
| title=title, | |
| description=description, | |
| article=article, | |
| examples=examples, | |
| interpretation=interpretation, | |
| enable_queue=enable_queue | |
| ) | |
| text_to_image_app.launch(share=True) | |