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="

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" 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)