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blondejade in your prompt to invoke the character.1from diffusers import StableDiffusionXLPipeline
2import torch
3
4pipe = StableDiffusionXLPipeline.from_pretrained(
5 "SG161222/RealVisXL_V5.0",
6 torch_dtype=torch.float16,
7).to("cuda")
8
9pipe.load_lora_weights("XaflocAI/BlondeJade-SDXL", weight_name="blondejade_sdxl_v1.safetensors")
10
11prompt = "blondejade, a woman in a white lace dress on a Paris street, golden hour, photorealistic, 85mm"
12image = pipe(prompt, num_inference_steps=30, guidance_scale=5.0).images[0]
13image.save("blondejade.png")blondejade_sdxl_v1.safetensors in your models/Lora folder and add
<lora:blondejade_sdxl_v1:0.8> (or the equivalent LoRA loader node) to your prompt
along with the trigger word blondejade. A weight of 0.7–0.9 works well.| Setting | Value |
|---|---|
| Base model | RealVisXL V5.0 (or any SDXL checkpoint) |
| Resolution | 1024×1024 (and SDXL-native buckets) |
| LoRA weight | 0.7 – 0.9 |
| Sampler / steps | DPM++ 2M Karras, 25–35 steps |
| CFG scale | 4 – 6 |
| Clip skip | 2 |
| Base model | RealVisXL V5.0 (SDXL 1.0) |
| Network | LoRA (networks.lora) |
| Rank / Alpha | 32 / 16 |
| Optimizer | Prodigy (LR 1.0, cosine, 100 warmup steps) |
| Resolution | 1024×1024, aspect-ratio bucketing (512–1536) |
| Dataset | 168 images (156 hi-res + 12 lo-res), DreamBooth-style |
| Steps | 4000 (epoch 5) |
| Precision | bf16, clip skip 2 |
| Trainer | kohya-ss sd-scripts |