[Bug]: Stable diffusion model failed to load

### Checklist

- [X] 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
- [X] The issue exists in the current version of the webui
- [X] The issue has not been reported before recently
- [ ] The issue has been reported before but has not been fixed yet

### What happened?

It shows "Stable diffusion model failed to load" in console, and can't load any model. I tried to start with the aaaki manager, and it show keep loading "forge finalize", and keep fail.

### Steps to reproduce the problem

1. Run the run.bat
2. The webui start up with no model, and an error symbol on the model panel.

### What should have happened?

Models should be loaded successfully.

### What browsers do you use to access the UI ?

Google Chrome

### Sysinfo

[sysinfo-2024-03-04-11-59.json](https://github.com/lllyasviel/stable-diffusion-webui-forge/files/14481103/sysinfo-2024-03-04-11-59.json)

### Console logs

```Shell
Stable diffusion model failed to load
Loading weights [879db523c3] from D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\models\Stable-diffusion\dreamshaper_8.safetensors
Traceback (most recent call last):
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\gradio\routes.py", line 488, in run_predict
output = await app.get_blocks().process_api(
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\gradio\blocks.py", line 1431, in process_api
result = await self.call_function(
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\gradio\blocks.py", line 1103, in call_function
prediction = await anyio.to_thread.run_sync(
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
return await get_asynclib().run_sync_in_worker_thread(
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\anyio\_backends\_asyncio.py", line 877, in run_sync_in_worker_thread
return await future
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
result = context.run(func, *args)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\gradio\utils.py", line 707, in wrapper
response = f(*args, **kwargs)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 703, in pages_html
create_html()
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 699, in create_html
ui.pages_contents = [pg.create_html(ui.tabname) for pg in ui.stored_extra_pages]
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 699, in
ui.pages_contents = [pg.create_html(ui.tabname) for pg in ui.stored_extra_pages]
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 518, in create_html
self.items = {x["name"]: x for x in items_list}
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 518, in
self.items = {x["name"]: x for x in items_list}
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\extensions-builtin\Lora\ui_extra_networks_lora.py", line 82, in list_items
item = self.create_item(name, index)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\extensions-builtin\Lora\ui_extra_networks_lora.py", line 69, in create_item
elif shared.sd_model.is_sdxl and sd_version != network.SdVersion.SDXL:
AttributeError: 'NoneType' object has no attribute 'is_sdxl'
model_type EPS
UNet ADM Dimension 0
Using pytorch attention in VAE
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
Using pytorch attention in VAE
extra {'cond_stage_model.clip_l.text_projection', 'cond_stage_model.clip_l.logit_scale'}
loaded straight to GPU
To load target model BaseModel
Begin to load 1 model
[Memory Management] Current Free GPU Memory (MB) = 1500.59033203125
[Memory Management] Model Memory (MB) = 0.00762939453125
[Memory Management] Minimal Inference Memory (MB) = 1024.0
[Memory Management] Estimated Remaining GPU Memory (MB) = 476.58270263671875
Moving model(s) has taken 0.01 seconds
Loading VAE weights specified in settings: D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\models\VAE\diffusion_pytorch_model.fp16.safetensors
loading stable diffusion model: RuntimeError
Traceback (most recent call last):
File "threading.py", line 973, in _bootstrap
File "threading.py", line 1016, in _bootstrap_inner
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
result = context.run(func, *args)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\gradio\utils.py", line 707, in wrapper
response = f(*args, **kwargs)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 703, in pages_html
create_html()
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 699, in create_html
ui.pages_contents = [pg.create_html(ui.tabname) for pg in ui.stored_extra_pages]
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 699, in
ui.pages_contents = [pg.create_html(ui.tabname) for pg in ui.stored_extra_pages]
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 518, in create_html
self.items = {x["name"]: x for x in items_list}
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 518, in
self.items = {x["name"]: x for x in items_list}
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\extensions-builtin\Lora\ui_extra_networks_lora.py", line 82, in list_items
item = self.create_item(name, index)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\extensions-builtin\Lora\ui_extra_networks_lora.py", line 69, in create_item
elif shared.sd_model.is_sdxl and sd_version != network.SdVersion.SDXL:
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\shared_items.py", line 133, in sd_model
return modules.sd_models.model_data.get_sd_model()
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\sd_models.py", line 509, in get_sd_model
load_model()
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\sd_models.py", line 599, in load_model
sd_vae.load_vae(sd_model, vae_file, vae_source)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\sd_vae.py", line 212, in load_vae
_load_vae_dict(model, vae_dict_1)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\sd_vae.py", line 239, in _load_vae_dict
model.first_stage_model.load_state_dict(vae_dict_1)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\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 AutoencoderKL:
Missing key(s) in state_dict: "encoder.down.0.block.0.norm1.weight", "encoder.down.0.block.0.norm1.bias", "encoder.down.0.block.0.conv1.weight", "encoder.down.0.block.0.conv1.bias", "encoder.down.0.block.0.norm2.weight", "encoder.down.0.block.0.norm2.bias", "encoder.down.0.block.0.conv2.weight", "encoder.down.0.block.0.conv2.bias", "encoder.down.0.block.1.norm1.weight", "encoder.down.0.block.1.norm1.bias", "encoder.down.0.block.1.conv1.weight", "encoder.down.0.block.1.conv1.bias", "encoder.down.0.block.1.norm2.weight", "encoder.down.0.block.1.norm2.bias", "encoder.down.0.block.1.conv2.weight", "encoder.down.0.block.1.conv2.bias", "encoder.down.0.downsample.conv.weight", "encoder.down.0.downsample.conv.bias", "encoder.down.1.block.0.norm1.weight", "encoder.down.1.block.0.norm1.bias", "encoder.down.1.block.0.conv1.weight", "encoder.down.1.block.0.conv1.bias", "encoder.down.1.block.0.norm2.weight", "encoder.down.1.block.0.norm2.bias", "encoder.down.1.block.0.conv2.weight", "encoder.down.1.block.0.conv2.bias", "encoder.down.1.block.0.nin_shortcut.weight", "encoder.down.1.block.0.nin_shortcut.bias", "encoder.down.1.block.1.norm1.weight", "encoder.down.1.block.1.norm1.bias", "encoder.down.1.block.1.conv1.weight", "encoder.down.1.block.1.conv1.bias", "encoder.down.1.block.1.norm2.weight", "encoder.down.1.block.1.norm2.bias", "encoder.down.1.block.1.conv2.weight", "encoder.down.1.block.1.conv2.bias", "encoder.down.1.downsample.conv.weight", "encoder.down.1.downsample.conv.bias", "encoder.down.2.block.0.norm1.weight", "encoder.down.2.block.0.norm1.bias", "encoder.down.2.block.0.conv1.weight", "encoder.down.2.block.0.conv1.bias", "encoder.down.2.block.0.norm2.weight", "encoder.down.2.block.0.norm2.bias", "encoder.down.2.block.0.conv2.weight", "encoder.down.2.block.0.conv2.bias", "encoder.down.2.block.0.nin_shortcut.weight", "encoder.down.2.block.0.nin_shortcut.bias", "encoder.down.2.block.1.norm1.weight", "encoder.down.2.block.1.norm1.bias", "encoder.down.2.block.1.conv1.weight", "encoder.down.2.block.1.conv1.bias", "encoder.down.2.block.1.norm2.weight", "encoder.down.2.block.1.norm2.bias", "encoder.down.2.block.1.conv2.weight", "encoder.down.2.block.1.conv2.bias", "encoder.down.2.downsample.conv.weight", "encoder.down.2.downsample.conv.bias", "encoder.down.3.block.0.norm1.weight", "encoder.down.3.block.0.norm1.bias", "encoder.down.3.block.0.conv1.weight", "encoder.down.3.block.0.conv1.bias", "encoder.down.3.block.0.norm2.weight", "encoder.down.3.block.0.norm2.bias", "encoder.down.3.block.0.conv2.weight", "encoder.down.3.block.0.conv2.bias", "encoder.down.3.block.1.norm1.weight", "encoder.down.3.block.1.norm1.bias", "encoder.down.3.block.1.conv1.weight", "encoder.down.3.block.1.conv1.bias", "encoder.down.3.block.1.norm2.weight", "encoder.down.3.block.1.norm2.bias", "encoder.down.3.block.1.conv2.weight", "encoder.down.3.block.1.conv2.bias", "encoder.mid.block_1.norm1.weight", "encoder.mid.block_1.norm1.bias", "encoder.mid.block_1.conv1.weight", "encoder.mid.block_1.conv1.bias", "encoder.mid.block_1.norm2.weight", "encoder.mid.block_1.norm2.bias", "encoder.mid.block_1.conv2.weight", "encoder.mid.block_1.conv2.bias", "encoder.mid.attn_1.norm.weight", "encoder.mid.attn_1.norm.bias", "encoder.mid.attn_1.q.weight", "encoder.mid.attn_1.q.bias", "encoder.mid.attn_1.k.weight", "encoder.mid.attn_1.k.bias", "encoder.mid.attn_1.v.weight", "encoder.mid.attn_1.v.bias", "encoder.mid.attn_1.proj_out.weight", "encoder.mid.attn_1.proj_out.bias", "encoder.mid.block_2.norm1.weight", "encoder.mid.block_2.norm1.bias", "encoder.mid.block_2.conv1.weight", "encoder.mid.block_2.conv1.bias", "encoder.mid.block_2.norm2.weight", "encoder.mid.block_2.norm2.bias", "encoder.mid.block_2.conv2.weight", "encoder.mid.block_2.conv2.bias", "encoder.norm_out.weight", "encoder.norm_out.bias", "decoder.mid.block_1.norm1.weight", "decoder.mid.block_1.norm1.bias", "decoder.mid.block_1.conv1.weight", "decoder.mid.block_1.conv1.bias", "decoder.mid.block_1.norm2.weight", "decoder.mid.block_1.norm2.bias", "decoder.mid.block_1.conv2.weight", "decoder.mid.block_1.conv2.bias", "decoder.mid.attn_1.norm.weight", "decoder.mid.attn_1.norm.bias", "decoder.mid.attn_1.q.weight", "decoder.mid.attn_1.q.bias", "decoder.mid.attn_1.k.weight", "decoder.mid.attn_1.k.bias", "decoder.mid.attn_1.v.weight", "decoder.mid.attn_1.v.bias", "decoder.mid.attn_1.proj_out.weight", "decoder.mid.attn_1.proj_out.bias", "decoder.mid.block_2.norm1.weight", "decoder.mid.block_2.norm1.bias", "decoder.mid.block_2.conv1.weight", "decoder.mid.block_2.conv1.bias", "decoder.mid.block_2.norm2.weight", "decoder.mid.block_2.norm2.bias", "decoder.mid.block_2.conv2.weight", "decoder.mid.block_2.conv2.bias", "decoder.up.0.block.0.norm1.weight", "decoder.up.0.block.0.norm1.bias", "decoder.up.0.block.0.conv1.weight", "decoder.up.0.block.0.conv1.bias", "decoder.up.0.block.0.norm2.weight", "decoder.up.0.block.0.norm2.bias", "decoder.up.0.block.0.conv2.weight", "decoder.up.0.block.0.conv2.bias", "decoder.up.0.block.0.nin_shortcut.weight", "decoder.up.0.block.0.nin_shortcut.bias", "decoder.up.0.block.1.norm1.weight", "decoder.up.0.block.1.norm1.bias", "decoder.up.0.block.1.conv1.weight", "decoder.up.0.block.1.conv1.bias", "decoder.up.0.block.1.norm2.weight", "decoder.up.0.block.1.norm2.bias", "decoder.up.0.block.1.conv2.weight", "decoder.up.0.block.1.conv2.bias", "decoder.up.0.block.2.norm1.weight", "decoder.up.0.block.2.norm1.bias", "decoder.up.0.block.2.conv1.weight", "decoder.up.0.block.2.conv1.bias", "decoder.up.0.block.2.norm2.weight", "decoder.up.0.block.2.norm2.bias", "decoder.up.0.block.2.conv2.weight", "decoder.up.0.block.2.conv2.bias", "decoder.up.1.block.0.norm1.weight", "decoder.up.1.block.0.norm1.bias", "decoder.up.1.block.0.conv1.weight", "decoder.up.1.block.0.conv1.bias", "decoder.up.1.block.0.norm2.weight", "decoder.up.1.block.0.norm2.bias", "decoder.up.1.block.0.conv2.weight", "decoder.up.1.block.0.conv2.bias", "decoder.up.1.block.0.nin_shortcut.weight", "decoder.up.1.block.0.nin_shortcut.bias", "decoder.up.1.block.1.norm1.weight", "decoder.up.1.block.1.norm1.bias", "decoder.up.1.block.1.conv1.weight", "decoder.up.1.block.1.conv1.bias", "decoder.up.1.block.1.norm2.weight", "decoder.up.1.block.1.norm2.bias", "decoder.up.1.block.1.conv2.weight", "decoder.up.1.block.1.conv2.bias", "decoder.up.1.block.2.norm1.weight", "decoder.up.1.block.2.norm1.bias", "decoder.up.1.block.2.conv1.weight", "decoder.up.1.block.2.conv1.bias", "decoder.up.1.block.2.norm2.weight", "decoder.up.1.block.2.norm2.bias", "decoder.up.1.block.2.conv2.weight", "decoder.up.1.block.2.conv2.bias", "decoder.up.1.upsample.conv.weight", "decoder.up.1.upsample.conv.bias", "decoder.up.2.block.0.norm1.weight", "decoder.up.2.block.0.norm1.bias", "decoder.up.2.block.0.conv1.weight", "decoder.up.2.block.0.conv1.bias", "decoder.up.2.block.0.norm2.weight", "decoder.up.2.block.0.norm2.bias", "decoder.up.2.block.0.conv2.weight", "decoder.up.2.block.0.conv2.bias", "decoder.up.2.block.1.norm1.weight", "decoder.up.2.block.1.norm1.bias", "decoder.up.2.block.1.conv1.weight", "decoder.up.2.block.1.conv1.bias", "decoder.up.2.block.1.norm2.weight", "decoder.up.2.block.1.norm2.bias", "decoder.up.2.block.1.conv2.weight", "decoder.up.2.block.1.conv2.bias", "decoder.up.2.block.2.norm1.weight", "decoder.up.2.block.2.norm1.bias", "decoder.up.2.block.2.conv1.weight", "decoder.up.2.block.2.conv1.bias", "decoder.up.2.block.2.norm2.weight", "decoder.up.2.block.2.norm2.bias", "decoder.up.2.block.2.conv2.weight", "decoder.up.2.block.2.conv2.bias", "decoder.up.2.upsample.conv.weight", "decoder.up.2.upsample.conv.bias", "decoder.up.3.block.0.norm1.weight", "decoder.up.3.block.0.norm1.bias", "decoder.up.3.block.0.conv1.weight", "decoder.up.3.block.0.conv1.bias", "decoder.up.3.block.0.norm2.weight", "decoder.up.3.block.0.norm2.bias", "decoder.up.3.block.0.conv2.weight", "decoder.up.3.block.0.conv2.bias", "decoder.up.3.block.1.norm1.weight", "decoder.up.3.block.1.norm1.bias", "decoder.up.3.block.1.conv1.weight", "decoder.up.3.block.1.conv1.bias", "decoder.up.3.block.1.norm2.weight", "decoder.up.3.block.1.norm2.bias", "decoder.up.3.block.1.conv2.weight", "decoder.up.3.block.1.conv2.bias", "decoder.up.3.block.2.norm1.weight", "decoder.up.3.block.2.norm1.bias", "decoder.up.3.block.2.conv1.weight", "decoder.up.3.block.2.conv1.bias", "decoder.up.3.block.2.norm2.weight", "decoder.up.3.block.2.norm2.bias", "decoder.up.3.block.2.conv2.weight", "decoder.up.3.block.2.conv2.bias", "decoder.up.3.upsample.conv.weight", "decoder.up.3.upsample.conv.bias", "decoder.norm_out.weight", "decoder.norm_out.bias".
Unexpected key(s) in state_dict: "encoder.conv_norm_out.bias", "encoder.conv_norm_out.weight", "encoder.down_blocks.0.downsamplers.0.conv.bias", "encoder.down_blocks.0.downsamplers.0.conv.weight", "encoder.down_blocks.0.resnets.0.conv1.bias", "encoder.down_blocks.0.resnets.0.conv1.weight", "encoder.down_blocks.0.resnets.0.conv2.bias", "encoder.down_blocks.0.resnets.0.conv2.weight", "encoder.down_blocks.0.resnets.0.norm1.bias", "encoder.down_blocks.0.resnets.0.norm1.weight", "encoder.down_blocks.0.resnets.0.norm2.bias", "encoder.down_blocks.0.resnets.0.norm2.weight", "encoder.down_blocks.0.resnets.1.conv1.bias", "encoder.down_blocks.0.resnets.1.conv1.weight", "encoder.down_blocks.0.resnets.1.conv2.bias", "encoder.down_blocks.0.resnets.1.conv2.weight", "encoder.down_blocks.0.resnets.1.norm1.bias", "encoder.down_blocks.0.resnets.1.norm1.weight", "encoder.down_blocks.0.resnets.1.norm2.bias", "encoder.down_blocks.0.resnets.1.norm2.weight", "encoder.down_blocks.1.downsamplers.0.conv.bias", "encoder.down_blocks.1.downsamplers.0.conv.weight", "encoder.down_blocks.1.resnets.0.conv1.bias", "encoder.down_blocks.1.resnets.0.conv1.weight", "encoder.down_blocks.1.resnets.0.conv2.bias", "encoder.down_blocks.1.resnets.0.conv2.weight", "encoder.down_blocks.1.resnets.0.conv_shortcut.bias", "encoder.down_blocks.1.resnets.0.conv_shortcut.weight", "encoder.down_blocks.1.resnets.0.norm1.bias", "encoder.down_blocks.1.resnets.0.norm1.weight", "encoder.down_blocks.1.resnets.0.norm2.bias", "encoder.down_blocks.1.resnets.0.norm2.weight", "encoder.down_blocks.1.resnets.1.conv1.bias", "encoder.down_blocks.1.resnets.1.conv1.weight", "encoder.down_blocks.1.resnets.1.conv2.bias", "encoder.down_blocks.1.resnets.1.conv2.weight", "encoder.down_blocks.1.resnets.1.norm1.bias", "encoder.down_blocks.1.resnets.1.norm1.weight", "encoder.down_blocks.1.resnets.1.norm2.bias", "encoder.down_blocks.1.resnets.1.norm2.weight", "encoder.down_blocks.2.downsamplers.0.conv.bias", 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Stable diffusion model failed to load
Traceback (most recent call last):
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\gradio\routes.py", line 488, in run_predict
output = await app.get_blocks().process_api(
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\gradio\blocks.py", line 1431, in process_api
result = await self.call_function(
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\gradio\blocks.py", line 1103, in call_function
prediction = await anyio.to_thread.run_sync(
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
return await get_asynclib().run_sync_in_worker_thread(
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\anyio\_backends\_asyncio.py", line 877, in run_sync_in_worker_thread
return await future
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
result = context.run(func, *args)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\system\python\lib\site-packages\gradio\utils.py", line 707, in wrapper
response = f(*args, **kwargs)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 703, in pages_html
create_html()
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 699, in create_html
ui.pages_contents = [pg.create_html(ui.tabname) for pg in ui.stored_extra_pages]
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 699, in
ui.pages_contents = [pg.create_html(ui.tabname) for pg in ui.stored_extra_pages]
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 518, in create_html
self.items = {x["name"]: x for x in items_list}
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\modules\ui_extra_networks.py", line 518, in
self.items = {x["name"]: x for x in items_list}
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\extensions-builtin\Lora\ui_extra_networks_lora.py", line 82, in list_items
item = self.create_item(name, index)
File "D:\Program Files\StableDiffusion\webui_forge_cu121_torch21\webui\extensions-builtin\Lora\ui_extra_networks_lora.py", line 69, in create_item
elif shared.sd_model.is_sdxl and sd_version != network.SdVersion.SDXL:
AttributeError: 'NoneType' object has no attribute 'is_sdxl'
```

### Additional information

The Console logs are split into two parts by spaces, the first part is repeated a few times, then the second part.
It didn't happen some times but I can't pinpoint what fixed it. It doesn't happen when I remove all models. I have ckpts of 175GB, loras of 19.9GB.
I've tried common solutions to this problem, add "--disable-safe-unpickle", update Graphics Driver, Increase the Virtual Memory, all doesn't work. And the A1111 webui doesn't have the problem, so I'm pretty sure thats a new bug with forge.
I have a guess that it might be affected by the currently loaded model, but it's hard to verify without being able to load any models.

Start with modules/sd_models.py, modules/sd_vae.py, and modules/ui_extra_networks.py, then reproduce the failure by running run.bat with the reported model and VAE files. Trace the state-dict loading error and the NoneType access in the console output; done means the model loads successfully without these errors.

Written by the indexing model from the issue text.