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import gradio as gr |
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import os |
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import spaces |
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import torch |
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from diffusers import DiffusionPipeline |
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pipeline = DiffusionPipeline.from_pretrained("segmind/tiny-sd") |
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pipeline.load_lora_weights( |
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"philipp-zettl/jon_juarez-lora", |
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hf_token=os.environ.get('HF_TOKEN') |
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) |
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pipe.to('cuda') |
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@spaces.GPU |
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def generate(prompt, negative_prompt, num_inference_steps, width, height): |
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return pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=num_inference_steps, width=width, height=height).images |
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app = gr.Interface( |
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fn=generate, |
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inputs=[ |
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gr.Text(label="Prompt"), |
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gr.Text("", label="Negative Prompt"), |
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gr.Number(45, label="Number inference steps"), |
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gr.Number(1024, label='image width'), |
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gr.Number(1024, label='image height'), |
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], |
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outputs=gr.Gallery(), |
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) |
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with app as demo: |
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demo.examples = [ |
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"Colorful line shading by JON_JUAREZ a dark cave with toxic mushrooms", |
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] |
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gr.Slider(label="seed") |
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demo.launch() |
