import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("olesheva/DavidLynch-Qwen-LoRA")
prompt = "-"
image = pipe(prompt).images[0]DavidLynch-LoRA
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Model description
This lora was trained for 90 epochs using onetrainer on a dataset of 63 high-res frames from Twin Peaks, Mulholland Drive, Blue Velvet etc. It focused on color grading, so no trigger words are required. For caption-based prompting I use qwen captioner to generate prompts for examples. Works normally on 1.0-1.2, you can mix it with another realism loras as well. Civit.ai:https://civitai.com/models/2044496?modelVersionId=2313953
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