huggingface / huggingface/diffusers
KeyError when loading LoRA for Flux model: missing lora_unet_final_layer_adaLN_modulation_1 weights
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Beschreibung
I'm trying to run Overlay-Kontext-Dev-LoRA locally by loading the LoRA weights using the pipe.load_lora_weights() function. However, I encountered the following error during execution:
> KeyError: 'lora_unet_final_layer_adaLN_modulation_1.lora_down.weight'
```
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image
Load the pipeline with a specific torch data type for GPU optimization
pipe = DiffusionPipeline.from_pretrained(
"black-forest-labs/FLUX.1-Kontext-dev",
torch_dtype=torch.bfloat16
)
Move the entire pipeline to the GPU
pipe.to("cuda")
Load LoRA weights (this will also be on the GPU)
pipe.load_lora_weights("ilkerzgi/Overlay-Kontext-Dev-LoRA")
prompt = "Place it"
input_image = load_image("img2.png")
The pipeline will now run on the GPU
image = pipe(image=input_image, prompt=prompt).images[0]
image.save("output_image.png")
```
Environment:
diffusers version: 0.35.0.dev0
Python: 3.10
Running locally on a ubuntu environment with RTX 4090
> Additional Note:
> The model file size is also quite large. I may need to quantize it before running it on the 4090 to avoid out-of-memory issues.
>
> Would appreciate any help or suggestions on how to resolve the loading issue. Thank you!
Beitragsleitfaden
Rechercherichtung
Start by reproducing the provided Python script with diffusers 0.35.0.dev0 and inspect the pipe.load_lora_weights() entry point using the Overlay-Kontext-Dev-LoRA and FLUX.1-Kontext-dev model. Compare the LoRA keys with the pipeline's expected keys, and consider the issue done when the weights load without the missing lora_unet_final_layer_adaLN_modulation_1 error.
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- Tech-Stack
- python, pytorch
- Bereich
- machine-learning
- Issue-Typ
- Bug
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- 3/5
- Geschätzter Aufwand
- 1-2 Tage
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- Veraltet
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- 35/100