Stability Matrix comfyui multiple errors on clean install.

### Your question

Hello I have an issue with comfyui, I downloaded it clean via stability matrix, at first I had issues with doing update since I always got an error but not I am sure it's the newest. The version of flux that I'm using is flux1-dev-bnb-nf4-v2.safetensors from https://huggingface.co/lllyasviel/flux1-dev-bnb-nf4/tree/main

### Logs

```powershell
# ComfyUI Error Report
## Error Details
- **Node ID:** 4
- **Node Type:** CheckpointLoaderSimple
- **Exception Type:** RuntimeError
- **Exception Message:** Error(s) in loading state_dict for Flux:
size mismatch for img_in.weight: copying a param with shape torch.Size([98304, 1]) from checkpoint, the shape in current model is torch.Size([3072, 0]).
size mismatch for time_in.in_layer.weight: copying a param with shape torch.Size([393216, 1]) from checkpoint, the shape in current model is torch.Size([3072, 256]).
size mismatch for time_in.out_layer.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for vector_in.in_layer.weight: copying a param with shape torch.Size([1179648, 1]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
size mismatch for vector_in.out_layer.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for guidance_in.in_layer.weight: copying a param with shape torch.Size([393216, 1]) from checkpoint, the shape in current model is torch.Size([3072, 256]).
size mismatch for guidance_in.out_layer.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for txt_in.weight: copying a param with shape torch.Size([6291456, 1]) from checkpoint, the shape in current model is torch.Size([3072, 4096]).
size mismatch for double_blocks.0.img_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.0.img_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.0.img_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.0.img_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([12288, 3072]).
size mismatch for double_blocks.0.img_mlp.2.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([3072, 12288]).
size mismatch for double_blocks.0.txt_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.0.txt_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.0.txt_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.0.txt_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([12288, 3072]).
size mismatch for double_blocks.0.txt_mlp.2.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([3072, 12288]).
size mismatch for double_blocks.1.img_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.1.img_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.1.img_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.1.img_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([12288, 3072]).
size mismatch for double_blocks.1.img_mlp.2.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([3072, 12288]).
size mismatch for double_blocks.1.txt_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.1.txt_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.1.txt_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.1.txt_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([12288, 3072]).
size mismatch for double_blocks.1.txt_mlp.2.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([3072, 12288]).
size mismatch for double_blocks.2.img_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.2.img_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.2.img_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.2.img_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([12288, 3072]).
size mismatch for double_blocks.2.img_mlp.2.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([3072, 12288]).
size mismatch for double_blocks.2.txt_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.2.txt_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.2.txt_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.2.txt_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([12288, 3072]).
size mismatch for double_blocks.2.txt_mlp.2.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([3072, 12288]).
size mismatch for double_blocks.3.img_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.3.img_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.3.img_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.3.img_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([12288, 3072]).
size mismatch for double_blocks.3.img_mlp.2.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([3072, 12288]).
size mismatch for double_blocks.3.txt_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.3.txt_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.3.txt_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.3.txt_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([12288, 3072]).
size mismatch for double_blocks.3.txt_mlp.2.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([3072, 12288]).
size mismatch for double_blocks.4.img_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.4.img_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for final_layer.linear.weight: copying a param with shape torch.Size([98304, 1]) from checkpoint, the shape in current model is torch.Size([64, 3072]).
size mismatch for final_layer.adaLN_modulation.1.weight: copying a param with shape torch.Size([9437184, 1]) from checkpoint, the shape in current model is torch.Size([6144, 3072]).
## Stack Trace

File "A:\Data\Packages\ComfyUI\execution.py", line 327, in execute
output_data, output_ui, has_subgraph = get_output_data(obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)

File "A:\Data\Packages\ComfyUI\execution.py", line 202, in get_output_data
return_values = _map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)

File "A:\Data\Packages\ComfyUI\execution.py", line 174, in _map_node_over_list
process_inputs(input_dict, i)

File "A:\Data\Packages\ComfyUI\execution.py", line 163, in process_inputs
results.append(getattr(obj, func)(**inputs))

File "A:\Data\Packages\ComfyUI\nodes.py", line 570, in load_checkpoint
out = comfy.sd.load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, embedding_directory=folder_paths.get_folder_paths("embeddings"))

File "A:\Data\Packages\ComfyUI\comfy\sd.py", line 849, in load_checkpoint_guess_config
out = load_state_dict_guess_config(sd, output_vae, output_clip, output_clipvision, embedding_directory, output_model, model_options, te_model_options=te_model_options)

File "A:\Data\Packages\ComfyUI\comfy\sd.py", line 890, in load_state_dict_guess_config
model.load_model_weights(sd, diffusion_model_prefix)

File "A:\Data\Packages\ComfyUI\comfy\model_base.py", line 253, in load_model_weights
m, u = self.diffusion_model.load_state_dict(to_load, strict=False)

File "A:\Data\Packages\ComfyUI\venv\lib\site-packages\torch\nn\modules\module.py", line 2584, in load_state_dict
raise RuntimeError(

## System Information
- **ComfyUI Version:** 0.3.12
- **Arguments:** A:\Data\Packages\ComfyUI\main.py --preview-method auto
- **OS:** nt
- **Python Version:** 3.10.11 (tags/v3.10.11:7d4cc5a, Apr 5 2023, 00:38:17) [MSC v.1929 64 bit (AMD64)]
- **Embedded Python:** false
- **PyTorch Version:** 2.5.1+cu124
## Devices

- **Name:** cuda:0 NVIDIA GeForce RTX 3090 : cudaMallocAsync
- **Type:** cuda
- **VRAM Total:** 25769279488
- **VRAM Free:** 24438112256
- **Torch VRAM Total:** 0
- **Torch VRAM Free:** 0

## Logs

2025-01-26T17:44:10.371484 - Adding extra search path checkpoints A:\Data\Models\StableDiffusion
2025-01-26T17:44:10.371484 - Adding extra search path vae A:\Data\Models\VAE
2025-01-26T17:44:10.371484 - Adding extra search path loras A:\Data\Models\Lora
2025-01-26T17:44:10.371484 - Adding extra search path loras A:\Data\Models\LyCORIS
2025-01-26T17:44:10.371484 - Adding extra search path upscale_models A:\Data\Models\ESRGAN
2025-01-26T17:44:10.371484 - Adding extra search path upscale_models A:\Data\Models\RealESRGAN
2025-01-26T17:44:10.371484 - Adding extra search path upscale_models A:\Data\Models\SwinIR
2025-01-26T17:44:10.371484 - Adding extra search path embeddings A:\Data\Models\TextualInversion
2025-01-26T17:44:10.371484 - Adding extra search path hypernetworks A:\Data\Models\Hypernetwork
2025-01-26T17:44:10.371484 - Adding extra search path controlnet A:\Data\Models\ControlNet
2025-01-26T17:44:10.371484 - Adding extra search path controlnet A:\Data\Models\T2IAdapter
2025-01-26T17:44:10.371484 - Adding extra search path clip A:\Data\Models\CLIP
2025-01-26T17:44:10.371484 - Adding extra search path clip_vision A:\Data\Models\InvokeClipVision
2025-01-26T17:44:10.371484 - Adding extra search path diffusers A:\Data\Models\Diffusers
2025-01-26T17:44:10.371484 - Adding extra search path gligen A:\Data\Models\GLIGEN
2025-01-26T17:44:10.371484 - Adding extra search path vae_approx A:\Data\Models\ApproxVAE
2025-01-26T17:44:10.371484 - Adding extra search path ipadapter A:\Data\Models\IpAdapter
2025-01-26T17:44:10.371484 - Adding extra search path ipadapter A:\Data\Models\InvokeIpAdapters15
2025-01-26T17:44:10.371484 - Adding extra search path ipadapter A:\Data\Models\InvokeIpAdaptersXl
2025-01-26T17:44:10.371484 - Adding extra search path prompt_expansion A:\Data\Models\PromptExpansion
2025-01-26T17:44:10.371484 - Adding extra search path ultralytics A:\Data\Models\Ultralytics
2025-01-26T17:44:10.371484 - Adding extra search path ultralytics_bbox A:\Data\Models\Ultralytics\bbox
2025-01-26T17:44:10.371484 - Adding extra search path ultralytics_segm A:\Data\Models\Ultralytics\segm
2025-01-26T17:44:10.371484 - Adding extra search path sams A:\Data\Models\Sams
2025-01-26T17:44:10.371484 - Adding extra search path diffusion_models A:\Data\Models\unet
2025-01-26T17:44:11.696539 - Checkpoint files will always be loaded safely.
2025-01-26T17:44:11.817143 - Total VRAM 24576 MB, total RAM 65315 MB
2025-01-26T17:44:11.817143 - pytorch version: 2.5.1+cu124
2025-01-26T17:44:11.817143 - Set vram state to: NORMAL_VRAM
2025-01-26T17:44:11.817143 - Device: cuda:0 NVIDIA GeForce RTX 3090 : cudaMallocAsync
2025-01-26T17:44:12.904498 - Using pytorch attention
2025-01-26T17:44:14.095681 - ComfyUI version: 0.3.12
2025-01-26T17:44:14.111631 - [Prompt Server] web root: A:\Data\Packages\ComfyUI\web
2025-01-26T17:44:14.397389 -
Import times for custom nodes:
2025-01-26T17:44:14.397389 - 0.0 seconds: A:\Data\Packages\ComfyUI\custom_nodes\websocket_image_save.py
2025-01-26T17:44:14.397389 -
2025-01-26T17:44:14.403338 - Starting server

2025-01-26T17:44:14.403338 - To see the GUI go to: http://127.0.0.1:8188
2025-01-26T17:44:47.144317 - got prompt
2025-01-26T17:44:47.283850 - model weight dtype torch.bfloat16, manual cast: None
2025-01-26T17:44:47.284847 - model_type FLUX
2025-01-26T17:44:47.313751 - !!! Exception during processing !!! Error(s) in loading state_dict for Flux:
size mismatch for img_in.weight: copying a param with shape torch.Size([98304, 1]) from checkpoint, the shape in current model is torch.Size([3072, 0]).
size mismatch for time_in.in_layer.weight: copying a param with shape torch.Size([393216, 1]) from checkpoint, the shape in current model is torch.Size([3072, 256]).
size mismatch for time_in.out_layer.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for vector_in.in_layer.weight: copying a param with shape torch.Size([1179648, 1]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
size mismatch for vector_in.out_layer.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for guidance_in.in_layer.weight: copying a param with shape torch.Size([393216, 1]) from checkpoint, the shape in current model is torch.Size([3072, 256]).
size mismatch for guidance_in.out_layer.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for txt_in.weight: copying a param with shape torch.Size([6291456, 1]) from checkpoint, the shape in current model is torch.Size([3072, 4096]).
size mismatch for double_blocks.0.img_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.0.img_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.0.img_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.0.img_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from
size mismatch for single_blocks.37.linear2.weight: copying a param with shape torch.Size([23592960, 1]) from checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.37.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for final_layer.linear.weight: copying a param with shape torch.Size([98304, 1]) from checkpoint, the shape in current model is torch.Size([64, 3072]).
size mismatch for final_layer.adaLN_modulation.1.weight: copying a param with shape torch.Size([9437184, 1]) from checkpoint, the shape in current model is torch.Size([6144, 3072]).
2025-01-26T17:44:47.317737 - Traceback (most recent call last):
File "A:\Data\Packages\ComfyUI\execution.py", line 327, in execute
output_data, output_ui, has_subgraph = get_output_data(obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
File "A:\Data\Packages\ComfyUI\execution.py", line 202, in get_output_data
return_values = _map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
File "A:\Data\Packages\ComfyUI\execution.py", line 174, in _map_node_over_list
process_inputs(input_dict, i)
File "A:\Data\Packages\ComfyUI\execution.py", line 163, in process_inputs
results.append(getattr(obj, func)(**inputs))
File "A:\Data\Packages\ComfyUI\nodes.py", line 570, in load_checkpoint
out = comfy.sd.load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, embedding_directory=folder_paths.get_folder_paths("embeddings"))
File "A:\Data\Packages\ComfyUI\comfy\sd.py", line 849, in load_checkpoint_guess_config
out = load_state_dict_guess_config(sd, output_vae, output_clip, output_clipvision, embedding_directory, output_model, model_options, te_model_options=te_model_options)
File "A:\Data\Packages\ComfyUI\comfy\sd.py", line 890, in load_state_dict_guess_config
model.load_model_weights(sd, diffusion_model_prefix)
File "A:\Data\Packages\ComfyUI\comfy\model_base.py", line 253, in load_model_weights
m, u = self.diffusion_model.load_state_dict(to_load, strict=False)
File "A:\Data\Packages\ComfyUI\venv\lib\site-packages\torch\nn\modules\module.py", line 2584, in load_state_dict
raise RuntimeError(
RuntimeError: Error(s) in loading state_dict for Flux:
size mismatch for img_in.weight: copying a param with shape torch.Size([98304, 1]) from checkpoint, the shape in current model is torch.Size([3072, 0]).
size mismatch for time_in.in_layer.weight: copying a param with shape torch.Size([393216, 1]) from checkpoint, the shape in current model is torch.Size([3072, 256]).
size mismatch for time_in.out_layer.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for vector_in.in_layer.weight: copying a param with shape torch.Size([1179648, 1]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
size mismatch for vector_in.out_layer.weight: copying a param with shape torch.Size([4718592, 1]) from
size mismatch for single_blocks.2.linear2.weight: copying a param with shape torch.Size([23592960, 1]) from checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.2.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for single_blocks.3.linear1.weight: copying a param with shape torch.Size([33030144, 1]) from checkpoint, the shape in current model is torch.Size([21504, 3072]).
size mismatch for single_blocks.3.linear2.weight: copying a param with shape torch.Size([23592960, 1]) from checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.3.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for single_blocks.4.linear1.weight: copying a param with shape torch.Size([33030144, 1]) from checkpoint, the shape in current model is torch.Size([21504, 3072]).
size mismatch for single_blocks.4.linear2.weight: copying a param with shape torch.Size([23592960, 1]) from checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.4.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for single_blocks.5.linear1.weight: copying a param with shape torch.Size([33030144, 1]) from checkpoint, the shape in current model is torch.Size([21504, 3072]).
size mismatch for single_blocks.5.linear2.weight: copying a param with shape torch.Size([23592960, 1]) from checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.5.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for single_blocks.6.linear1.weight: copying a param with shape torch.Size([33030144, 1]) from checkpoint, the shape in current model is torch.Size([21504, 3072]).
size mismatch for single_blocks.6.linear2.weight: copying a param with shape torch.Size([23592960, 1]) from checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.6.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for single_blocks.7.linear1.weight: copying a param with shape torch.Size([33030144, 1]) from checkpoint, the shape in current model is torch.Size([21504, 3072]).
size mismatch for single_blocks.7.linear2.weight: copying a param with shape torch.Size([23592960, 1]) from checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.7.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for single_blocks.8.linear1.weight: copying a param with shape torch.Size([33030144, 1]) from checkpoint, the shape in current model is torch.Size([21504, 3072]).
size mismatch for single_blocks.8.linear2.weight: copying a param with shape torch.Size([23592960, 1]) from checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.8.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for single_blocks.9.linear1.weight: copying a param with shape torch.Size([33030144, 1]) from checkpoint, the shape in current model is torch.Size([21504, 3072]).
size mismatch for single_blocks.9.linear2.weight: copying a param with shape torch.Size([23592960, 1]) from checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.9.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for single_blocks.10.linear1.weight: copying a param with shape torch.Size([33030144, 1]) from checkpoint, the shape in current model is torch.Size([21504, 3072]).
size mismatch for single_blocks.10.linear2.weight: copying a param with shape torch.Size([23592960, 1]) from checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.10.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for final_layer.linear.weight: copying a param with shape torch.Size([98304, 1]) from checkpoint, the shape in current model is torch.Size([64, 3072]).
size mismatch for final_layer.adaLN_modulation.1.weight: copying a param with shape torch.Size([9437184, 1]) from checkpoint, the shape in current model is torch.Size([6144, 3072]).

2025-01-26T17:44:47.320727 - Prompt executed in 0.17 seconds
2025-01-26T17:51:22.533245 - got prompt
2025-01-26T17:51:22.819288 - model weight dtype torch.bfloat16, manual cast: None
2025-01-26T17:51:22.819288 - model_type FLUX
2025-01-26T17:51:22.848192 - !!! Exception during processing !!! Error(s) in loading state_dict for Flux:
size mismatch for img_in.weight: copying a param with shape torch.Size([98304, 1]) from checkpoint, the shape in current model is torch.Size([3072, 0]).
size mismatch for time_in.in_layer.weight: copying a param with shape torch.Size([393216, 1]) from checkpoint, the shape in current model is torch.Size([3072, 256]).
size mismatch for time_in.out_layer.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for vector_in.in_layer.weight: copying a param with shape torch.Size([1179648, 1]) from checkpoint, the shape in current model is torch.Size([3072, 768]).
size mismatch for vector_in.out_layer.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for guidance_in.in_layer.weight: copying a param with shape torch.Size([393216, 1]) from checkpoint, the shape in current model is torch.Size([3072, 256]).
size mismatch for guidance_in.out_layer.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for txt_in.weight: copying a param with shape torch.Size([6291456, 1]) from checkpoint, the shape in current model is torch.Size([3072, 4096]).
size mismatch for double_blocks.0.img_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.0.img_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.0.img_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.0.img_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([12288, 3072]).
size mismatch for double_blocks.0.img_mlp.2.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([3072, 12288]).
size mismatch for double_blocks.0.txt_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.0.txt_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.0.txt_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.0.txt_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([12288, 3072]).
size mismatch for double_blocks.0.txt_mlp.2.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([3072, 12288]).
size mismatch for double_blocks.1.img_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from checkpoint, the shape in current model is torch.Size([18432, 3072]).
size mismatch for double_blocks.1.img_attn.qkv.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for double_blocks.1.img_attn.proj.weight: copying a param with shape torch.Size([4718592, 1]) from checkpoint, the shape in current model is torch.Size([3072, 3072]).
size mismatch for double_blocks.1.img_mlp.0.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([12288, 3072]).
size mismatch for double_blocks.1.img_mlp.2.weight: copying a param with shape torch.Size([18874368, 1]) from checkpoint, the shape in current model is torch.Size([3072, 12288]).
size mismatch for double_blocks.1.txt_mod.lin.weight: copying a param with shape torch.Size([28311552, 1]) from
size mismatch for single_blocks.36.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for single_blocks.37.linear1.weight: copying a param with shape torch.Size([33030144, 1]) from checkpoint, the shape in current model is torch.Size([21504, 3072]).
size mismatch for single_blocks.37.linear2.weight: copying a param with shape torch.Size([23592960, 1]) from checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.37.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) from checkpoint, the shape in current model is torch.Size([9216, 3072]).
size mismatch for final_layer.linear.weight: copying a param with shape torch.Size([98304, 1]) from checkpoint, the shape in current model is torch.Size([64, 3072]).
size mismatch for final_layer.adaLN_modulation.1.weight: copying a param with shape torch.Size([9437184, 1]) from checkpoint, the shape in current model is torch.Size([6144, 3072]).

2025-01-26T17:51:22.857161 - Prompt executed in 0.32 seconds

## Attached Workflow
Please make sure that workflow does not contain any sensitive information such as API keys or passwords.

{"last_node_id":10,"last_link_id":9,"nodes":[{"id":3,"type":"KSampler","pos":[863,186],"size":[315,262],"flags":{},"order":5,"mode":0,"inputs":[{"name":"model","type":"MODEL","link":1},{"name":"positive","type":"CONDITIONING","link":4},{"name":"negative","type":"CONDITIONING","link":6},{"name":"latent_image","type":"LATENT","link":2}],"outputs":[{"name":"LATENT","type":"LATENT","links":[7],"slot_index":0}],"properties":{"Node name for S&R":"KSampler"},"widgets_values":[962452822958925,"randomize",10,8,"euler","normal",1]},{"id":9,"type":"SaveImage","pos":[1451,189],"size":[210,58],"flags":{},"order":7,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":9}],"outputs":[],"properties":{},"widgets_values":["ComfyUI"]},{"id":5,"type":"EmptyLatentImage","pos":[521,673],"size":[315,106],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"LATENT","type":"LATENT","links":[2],"slot_index":0}],"properties":{"Node name for S&R":"EmptyLatentImage"},"widgets_values":[512,512,1]},{"id":8,"type":"VAEDecode","pos":[1209,188],"size":[210,46],"flags":{"collapsed":false},"order":6,"mode":0,"inputs":[{"name":"samples","type":"LATENT","link":7},{"name":"vae","type":"VAE","link":8}],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[9],"slot_index":0}],"properties":{"Node name for S&R":"VAEDecode"},"widgets_values":[]},{"id":10,"type":"LoadImage","pos":[424,239],"size":[315,314],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"IMAGE","type":"IMAGE","links":null},{"name":"MASK","type":"MASK","links":null}],"properties":{"Node name for S&R":"LoadImage"},"widgets_values":["pasted/image.png","image"]},{"id":7,"type":"CLIPTextEncode","pos":[413,389],"size":[425.27801513671875,180.6060791015625],"flags":{},"order":4,"mode":0,"inputs":[{"name":"clip","type":"CLIP","link":5}],"outputs":[{"name":"CONDITIONING","type":"CONDITIONING","links":[6],"slot_index":0}],"properties":{"Node name for S&R":"CLIPTextEncode"},"widgets_values":["text, watermark"]},{"id":6,"type":"CLIPTextEncode","pos":[415,186],"size":[422.84503173828125,164.31304931640625],"flags":{},"order":3,"mode":0,"inputs":[{"name":"clip","type":"CLIP","link":3}],"outputs":[{"name":"CONDITIONING","type":"CONDITIONING","links":[4],"slot_index":0}],"properties":{"Node name for S&R":"CLIPTextEncode"},"widgets_values":["horny succubus with a red skin"]},{"id":4,"type":"CheckpointLoaderSimple","pos":[51,317],"size":[315,98],"flags":{"collapsed":false},"order":2,"mode":0,"inputs":[],"outputs":[{"name":"MODEL","type":"MODEL","links":[1],"slot_index":0},{"name":"CLIP","type":"CLIP","links":[3,5],"slot_index":1},{"name":"VAE","type":"VAE","links":[8],"slot_index":2}],"properties":{"Node name for S&R":"CheckpointLoaderSimple"},"widgets_values":["flux1-dev-bnb-nf4-v2.safetensors"]}],"links":[[1,4,0,3,0,"MODEL"],[2,5,0,3,3,"LATENT"],[3,4,1,6,0,"CLIP"],[4,6,0,3,1,"CONDITIONING"],[5,4,1,7,0,"CLIP"],[6,7,0,3,2,"CONDITIONING"],[7,3,0,8,0,"LATENT"],[8,4,2,8,1,"VAE"],[9,8,0,9,0,"IMAGE"]],"groups":[],"config":{},"extra":{"ds":{"scale":1,"offset":[469,220]}},"version":0.4}
```

### Other

I deleted a lot of lines with for example from the logs like "checkpoint, the shape in current model is torch.Size([3072, 15360]).
size mismatch for single_blocks.2.modulation.lin.weight: copying a param with shape torch.Size([14155776, 1]) "