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Browse files- app.py +27 -0
- requirements.txt +6 -0
app.py
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# gradio_app.py
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import torch
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from diffusers import DiffusionPipeline
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import gradio as gr
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# Load model
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pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16)
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pipe.to("cuda")
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pipe.load_lora_weights("EliKet/train_text_to_img")
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# Generation function
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def generate_image(prompt):
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image = pipe(prompt).images[0]
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return image
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# Gradio Interface
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demo = gr.Interface(
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fn=generate_image,
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inputs=gr.Textbox(lines=2, placeholder="Enter your image prompt here..."),
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outputs="image",
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title="🐾 Lynx Text-to-Image Generator",
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description="Type a prompt (e.g., 'A majestic lynx in a snowy forest') and get an AI-generated image using Stable Diffusion + LoRA."
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)
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# Launch app
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demo.launch()
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requirements.txt
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torch>=2.0
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transformers>=4.36.0
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diffusers>=0.25.0
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accelerate
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gradio
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safetensors
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