stable-diffusion-webui
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AUTOMATIC1111
changing setting sd_model_checkpoint to SD3\sd3_medium.safetensors [cc236278d2]: RuntimeError
Checklist
- [ ] The issue exists after disabling all extensions
- [ ] The issue exists on a clean installation of webui
- [ ] The issue is caused by an extension, but I believe it is caused by a bug in the webui
- [ ] The issue exists in the current version of the webui
- [ ] The issue has not been reported before recently
- [ ] The issue has been reported before but has not been fixed yet
What happened?
E:\sd-webui-aki\sd-webui-aki-v4\configs\sd3-inference.yaml
Loading VAE weights specified in settings: E:\sd-webui-aki\sd-webui-aki-v4\models\VAE\sdxl_vae.safetensors
changing setting sd_model_checkpoint to SD3\sd3_medium.safetensors [cc236278d2]: RuntimeError
Traceback (most recent call last):
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\options.py", line 165, in set
option.onchange()
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\call_queue.py", line 14, in f
res = func(*args, **kwargs)
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\initialize_util.py", line 181, in
Steps to reproduce the problem
start webui -->Switching Models to SD3
What should have happened?
start webui
What browsers do you use to access the UI ?
No response
Sysinfo
win11 py3.10
Console logs
E:\sd-webui-aki\sd-webui-aki-v4\configs\sd3-inference.yaml
Loading VAE weights specified in settings: E:\sd-webui-aki\sd-webui-aki-v4\models\VAE\sdxl_vae.safetensors
changing setting sd_model_checkpoint to SD3\sd3_medium.safetensors [cc236278d2]: RuntimeError
Traceback (most recent call last):
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\options.py", line 165, in set
option.onchange()
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\call_queue.py", line 14, in f
res = func(*args, **kwargs)
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\initialize_util.py", line 181, in <lambda>
shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: sd_models.reload_model_weights()), call=False)
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_models.py", line 977, in reload_model_weights
load_model(checkpoint_info, already_loaded_state_dict=state_dict)
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_models.py", line 845, in load_model
load_model_weights(sd_model, checkpoint_info, state_dict, timer)
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_models.py", line 538, in load_model_weights
sd_vae.load_vae(model, vae_file, vae_source)
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_vae.py", line 212, in load_vae
_load_vae_dict(model, vae_dict_1)
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_vae.py", line 239, in _load_vae_dict
model.first_stage_model.load_state_dict(vae_dict_1)
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_disable_initialization.py", line 223, in <lambda>
module_load_state_dict = self.replace(torch.nn.Module, 'load_state_dict', lambda *args, **kwargs: load_state_dict(module_load_state_dict, *args, **kwargs))
File "E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_disable_initialization.py", line 221, in load_state_dict
original(module, state_dict, strict=strict)
File "E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 2152, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for SDVAE:
Unexpected key(s) in state_dict: "post_quant_conv.bias", "post_quant_conv.weight", "quant_conv.bias", "quant_conv.weight".
size mismatch for encoder.conv_out.weight: copying a param with shape torch.Size([8, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 512, 3, 3]).
size mismatch for encoder.conv_out.bias: copying a param with shape torch.Size([8]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for decoder.conv_in.weight: copying a param with shape torch.Size([512, 4, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 16, 3, 3]).
Additional information
No response
Same with Ubuntu 22.04:
Loading weights [cc236278d2] from /home/alexander/stable-diffusion-webui/models/Stable-diffusion/sd3_medium.safetensors Creating model from config: /home/alexander/stable-diffusion-webui/configs/sd3-inference.yaml Loading VAE weights specified in settings: /home/alexander/stable-diffusion-webui/models/VAE/sdxl.vae.safetensors changing setting sd_model_checkpoint to sd3_medium.safetensors [cc236278d2]: RuntimeError Traceback (most recent call last): File "/home/alexander/stable-diffusion-webui/modules/options.py", line 165, in set option.onchange() File "/home/alexander/stable-diffusion-webui/modules/call_queue.py", line 14, in f res = func(*args, **kwargs) File "/home/alexander/stable-diffusion-webui/modules/initialize_util.py", line 181, in <lambda> shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: sd_models.reload_model_weights()), call=False) File "/home/alexander/stable-diffusion-webui/modules/sd_models.py", line 977, in reload_model_weights load_model(checkpoint_info, already_loaded_state_dict=state_dict) File "/home/alexander/stable-diffusion-webui/modules/sd_models.py", line 845, in load_model load_model_weights(sd_model, checkpoint_info, state_dict, timer) File "/home/alexander/stable-diffusion-webui/modules/sd_models.py", line 538, in load_model_weights sd_vae.load_vae(model, vae_file, vae_source) File "/home/alexander/stable-diffusion-webui/modules/sd_vae.py", line 212, in load_vae _load_vae_dict(model, vae_dict_1) File "/home/alexander/stable-diffusion-webui/modules/sd_vae.py", line 239, in _load_vae_dict model.first_stage_model.load_state_dict(vae_dict_1) File "/home/alexander/stable-diffusion-webui/modules/sd_disable_initialization.py", line 223, in <lambda> module_load_state_dict = self.replace(torch.nn.Module, 'load_state_dict', lambda *args, **kwargs: load_state_dict(module_load_state_dict, *args, **kwargs)) File "/home/alexander/stable-diffusion-webui/modules/sd_disable_initialization.py", line 221, in load_state_dict original(module, state_dict, strict=strict) File "/home/alexander/.local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 2152, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for SDVAE: Unexpected key(s) in state_dict: "post_quant_conv.bias", "post_quant_conv.weight", "quant_conv.bias", "quant_conv.weight". size mismatch for encoder.conv_out.weight: copying a param with shape torch.Size([8, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 512, 3, 3]). size mismatch for encoder.conv_out.bias: copying a param with shape torch.Size([8]) from checkpoint, the shape in current model is torch.Size([32]). size mismatch for decoder.conv_in.weight: copying a param with shape torch.Size([512, 4, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 16, 3, 3]).
I solved this by going to Settings / VAE and setting the VAE to None. I think non-SD3 VAE's aren't compatible with SD3.
我通过转到“设置/ VAE”并将VAE设置为“无”来解决了这个问题。我认为非 SD3 VAE 与 SD3 不兼容。
I used this setting, but it still doesn't take effect
SD VAE is set to NONE and I get
Loading weights [11fe06e223] from D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\models\Stable-diffusion\best\stableDiffusion35_medium.safetensors
Creating model from config: D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\configs\sd3-inference.yaml
changing setting sd_model_checkpoint to best\stableDiffusion35_medium.safetensors: RuntimeError
Traceback (most recent call last):
File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\options.py", line 165, in set
option.onchange()
File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\call_queue.py", line 14, in f
res = func(*args, **kwargs)
File "d:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\initialize_util.py", line 181, in <lambda>
shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: sd_models.reload_model_weights()), call=False)
File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_models.py", line 977, in reload_model_weights
load_model(checkpoint_info, already_loaded_state_dict=state_dict)
File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_models.py", line 845, in load_model
load_model_weights(sd_model, checkpoint_info, state_dict, timer)
File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_models.py", line 440, in load_model_weights
model.load_state_dict(state_dict, strict=False)
File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_disable_initialization.py", line 223, in <lambda>
module_load_state_dict = self.replace(torch.nn.Module, 'load_state_dict', lambda *args, **kwargs: load_state_dict(module_load_state_dict, *args, **kwargs))
File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_disable_initialization.py", line 221, in load_state_dict
original(module, state_dict, strict=strict)
File "d:\projects\github\AUTOMATIC1111\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 2152, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for SD3Inferencer:
size mismatch for model.diffusion_model.joint_blocks.0.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.0.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.1.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.1.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.2.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.2.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.3.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.3.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.4.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.4.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.5.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.5.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.6.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.6.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.7.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.7.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.8.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.8.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.9.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.9.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.10.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.10.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.11.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.11.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.12.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.12.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
SD VAE is set to NONE and I get
Loading weights [11fe06e223] from D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\models\Stable-diffusion\best\stableDiffusion35_medium.safetensors Creating model from config: D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\configs\sd3-inference.yaml changing setting sd_model_checkpoint to best\stableDiffusion35_medium.safetensors: RuntimeError Traceback (most recent call last): File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\options.py", line 165, in set option.onchange() File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\call_queue.py", line 14, in f res = func(*args, **kwargs) File "d:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\initialize_util.py", line 181, in <lambda> shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: sd_models.reload_model_weights()), call=False) File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_models.py", line 977, in reload_model_weights load_model(checkpoint_info, already_loaded_state_dict=state_dict) File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_models.py", line 845, in load_model load_model_weights(sd_model, checkpoint_info, state_dict, timer) File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_models.py", line 440, in load_model_weights model.load_state_dict(state_dict, strict=False) File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_disable_initialization.py", line 223, in <lambda> module_load_state_dict = self.replace(torch.nn.Module, 'load_state_dict', lambda *args, **kwargs: load_state_dict(module_load_state_dict, *args, **kwargs)) File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_disable_initialization.py", line 221, in load_state_dict original(module, state_dict, strict=strict) File "d:\projects\github\AUTOMATIC1111\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 2152, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for SD3Inferencer: size mismatch for model.diffusion_model.joint_blocks.0.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.0.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.1.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.1.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.2.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.2.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.3.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.3.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.4.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.4.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.5.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.5.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.6.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.6.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.7.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.7.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.8.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.8.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.9.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.9.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.10.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.10.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.11.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.11.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.12.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.12.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
Can you please tell me if this problem is solved? I had a problem with the same issue.
Loading weights [11fe06e223] from /home/Data_Storage2/user/stable-diffusion-webui/models/Stable-diffusion/sd3.5_medium.safetensors
Creating model from config: /home/Data_Storage2/user/stable-diffusion-webui/configs/sd3-inference.yaml
changing setting sd_model_checkpoint to sd3.5_medium.safetensors [11fe06e223]: RuntimeError
Traceback (most recent call last):
File "/home/Data_Storage2/user/stable-diffusion-webui/modules/options.py", line 165, in set
option.onchange()
File "/home/Data_Storage2/user/stable-diffusion-webui/modules/call_queue.py", line 14, in f
res = func(*args, **kwargs)
File "/home/Data_Storage2/user/stable-diffusion-webui/modules/initialize_util.py", line 181, in <lambda>
shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: sd_models.reload_model_weights()), call=False)
File "/home/Data_Storage2/user/stable-diffusion-webui/modules/sd_models.py", line 977, in reload_model_weights
load_model(checkpoint_info, already_loaded_state_dict=state_dict)
File "/home/Data_Storage2/user/stable-diffusion-webui/modules/sd_models.py", line 845, in load_model
load_model_weights(sd_model, checkpoint_info, state_dict, timer)
File "/home/Data_Storage2/user/stable-diffusion-webui/modules/sd_models.py", line 440, in load_model_weights
model.load_state_dict(state_dict, strict=False)
File "/home/Data_Storage2/user/stable-diffusion-webui/modules/sd_disable_initialization.py", line 223, in <lambda>
module_load_state_dict = self.replace(torch.nn.Module, 'load_state_dict', lambda *args, **kwargs: load_state_dict(module_load_state_dict, *args, **kwargs))
File "/home/Data_Storage2/user/stable-diffusion-webui/modules/sd_disable_initialization.py", line 221, in load_state_dict
original(module, state_dict, strict=strict)
File "/home/pc/anaconda3/envs/sdwebui/lib/python3.10/site-packages/torch/nn/modules/module.py", line 2215, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for SD3Inferencer:
size mismatch for model.diffusion_model.joint_blocks.0.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.0.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.1.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.1.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.2.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.2.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.3.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.3.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.4.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.4.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.5.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.5.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.6.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.6.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.7.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.7.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.8.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.8.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.9.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.9.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.10.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.10.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.11.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.11.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for model.diffusion_model.joint_blocks.12.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]).
size mismatch for model.diffusion_model.joint_blocks.12.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
SD VAE is set to NONE and I get
Loading weights [11fe06e223] from D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\models\Stable-diffusion\best\stableDiffusion35_medium.safetensors Creating model from config: D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\configs\sd3-inference.yaml changing setting sd_model_checkpoint to best\stableDiffusion35_medium.safetensors: RuntimeError Traceback (most recent call last): File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\options.py", line 165, in set option.onchange() File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\call_queue.py", line 14, in f res = func(*args, **kwargs) File "d:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\initialize_util.py", line 181, in <lambda> shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: sd_models.reload_model_weights()), call=False) File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_models.py", line 977, in reload_model_weights load_model(checkpoint_info, already_loaded_state_dict=state_dict) File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_models.py", line 845, in load_model load_model_weights(sd_model, checkpoint_info, state_dict, timer) File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_models.py", line 440, in load_model_weights model.load_state_dict(state_dict, strict=False) File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_disable_initialization.py", line 223, in <lambda> module_load_state_dict = self.replace(torch.nn.Module, 'load_state_dict', lambda *args, **kwargs: load_state_dict(module_load_state_dict, *args, **kwargs)) File "D:\projects\github\AUTOMATIC1111\stable-diffusion-webui\modules\sd_disable_initialization.py", line 221, in load_state_dict original(module, state_dict, strict=strict) File "d:\projects\github\AUTOMATIC1111\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 2152, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for SD3Inferencer: size mismatch for model.diffusion_model.joint_blocks.0.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.0.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.1.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.1.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.2.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.2.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.3.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.3.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.4.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.4.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.5.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.5.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.6.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.6.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.7.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.7.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.8.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.8.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.9.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.9.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.10.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.10.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.11.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.11.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.12.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.12.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
Can you please tell me if this problem is solved? I had a problem with the same issue.
Loading weights [11fe06e223] from /home/Data_Storage2/user/stable-diffusion-webui/models/Stable-diffusion/sd3.5_medium.safetensors Creating model from config: /home/Data_Storage2/user/stable-diffusion-webui/configs/sd3-inference.yaml changing setting sd_model_checkpoint to sd3.5_medium.safetensors [11fe06e223]: RuntimeError Traceback (most recent call last): File "/home/Data_Storage2/user/stable-diffusion-webui/modules/options.py", line 165, in set option.onchange() File "/home/Data_Storage2/user/stable-diffusion-webui/modules/call_queue.py", line 14, in f res = func(*args, **kwargs) File "/home/Data_Storage2/user/stable-diffusion-webui/modules/initialize_util.py", line 181, in
shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: sd_models.reload_model_weights()), call=False) File "/home/Data_Storage2/user/stable-diffusion-webui/modules/sd_models.py", line 977, in reload_model_weights load_model(checkpoint_info, already_loaded_state_dict=state_dict) File "/home/Data_Storage2/user/stable-diffusion-webui/modules/sd_models.py", line 845, in load_model load_model_weights(sd_model, checkpoint_info, state_dict, timer) File "/home/Data_Storage2/user/stable-diffusion-webui/modules/sd_models.py", line 440, in load_model_weights model.load_state_dict(state_dict, strict=False) File "/home/Data_Storage2/user/stable-diffusion-webui/modules/sd_disable_initialization.py", line 223, in module_load_state_dict = self.replace(torch.nn.Module, 'load_state_dict', lambda *args, **kwargs: load_state_dict(module_load_state_dict, *args, **kwargs)) File "/home/Data_Storage2/user/stable-diffusion-webui/modules/sd_disable_initialization.py", line 221, in load_state_dict original(module, state_dict, strict=strict) File "/home/pc/anaconda3/envs/sdwebui/lib/python3.10/site-packages/torch/nn/modules/module.py", line 2215, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for SD3Inferencer: size mismatch for model.diffusion_model.joint_blocks.0.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.0.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.1.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.1.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.2.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.2.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.3.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.3.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.4.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.4.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.5.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.5.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.6.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.6.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.7.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.7.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.8.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.8.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.9.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.9.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.10.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.10.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.11.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.11.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]). size mismatch for model.diffusion_model.joint_blocks.12.x_block.adaLN_modulation.1.weight: copying a param with shape torch.Size([13824, 1536]) from checkpoint, the shape in current model is torch.Size([9216, 1536]). size mismatch for model.diffusion_model.joint_blocks.12.x_block.adaLN_modulation.1.bias: copying a param with shape torch.Size([13824]) from checkpoint, the shape in current model is torch.Size([9216]).
This is the use of sd3.5 model on stable-diffusion-webui reported an error, can not use sd3.5 model. Could you please post an official tutorial on this?