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  A 512x512 unconditional ImageNet diffusion model, fine-tuned for 900.000 samples from the 512x512 unconditional ImageNet diffusion model. It was fine-tuned using 60.000 images of architecture of the AIDA dataset from Harvard x ArchDaily.
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- ## Config (as used in Disco Diffusion)
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- {
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- "attention_resolutions": '32, 16, 8',
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- "class_cond": False,
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- "diffusion_steps": 1000,
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- "image_size": 512,
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- "learn_sigma": True,
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- "noise_schedule": "linear",
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- "num_channels": 256,
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- "num_head_channels": 64,
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- "num_res_blocks": 2,
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- "resblock_updown": True,
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- "rescale_timesteps": True,
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- "timestep_respacing": "250",
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- "use_scale_shift_norm": True
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- }
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  ---
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  license: cc
 
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  A 512x512 unconditional ImageNet diffusion model, fine-tuned for 900.000 samples from the 512x512 unconditional ImageNet diffusion model. It was fine-tuned using 60.000 images of architecture of the AIDA dataset from Harvard x ArchDaily.
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  ---
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  license: cc