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| import torch | |
| import modules.scripts as scripts | |
| import gradio as gr | |
| from modules.processing import StableDiffusionProcessing, process_images | |
| class Script(scripts.Script): | |
| def __init__(self): | |
| pass |
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| import torch | |
| import modules.scripts as scripts | |
| import gradio as gr | |
| from modules.processing import StableDiffusionProcessing, process_images | |
| class Script(scripts.Script): | |
| def __init__(self): | |
| pass |
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| ============================================================================================================== | |
| Layer (type (var_name)) Input Shape Output Shape | |
| ============================================================================================================== | |
| UNetModel (UNetModel) [1, 4, 64, 64] [1, 4, 64, 64] | |
| ├─Sequential (time_embed) [1, 320] [1, 1280] | |
| │ └─Linear (0) [1, 320] [1, 1280] | |
| │ └─SiLU (1) [1, 1280] [1, 1280] | |
| │ └─Linear (2) [1, 1280] [1, 1280] | |
| ├─ModuleList (input_blocks) -- -- | |
| │ └─TimestepEmbedSequential (0) [1, 4, 64, 64] [1, 320, 64, 64] |
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| #Put it on stable-diffusion-webui/scripts | |
| #Idea:https://twitter.com/Birchlabs/status/1640033271512702977 | |
| #Related to https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/9129 | |
| import torch | |
| import modules.scripts as scripts | |
| import gradio as gr | |
| from modules.script_callbacks import CFGDenoiserParams, on_cfg_denoiser, CFGDenoisedParams, on_cfg_denoised | |
| from modules.processing import StableDiffusionProcessing, process_images |
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| ''' | |
| It supports only SD-v2 models. | |
| usage: | |
| python simo2kohya.py --unet <simo's unet weight path> --text <simo's text_encoder weight path> --save_to <save path> | |
| (--text is optional) | |
| This code may no longer be available due to updates from both @kohya-ss and @cloneofsimo. | |
| ''' |
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