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ajaynegi0079/serene-sdxl-lora
serene-sdxl-lora is a text-to-image model from ajaynegi0079. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as cc-by-nc-4.0.
A custom SDXL LoRA that renders a consistent brand-ambassador likeness named Serene. Trained on a small curated dataset for use as a recurring face across social-media campaigns.
Downloads · 30 days
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From the Hugging Face model README
A custom SDXL LoRA that renders a consistent brand-ambassador likeness named Serene. Trained on a small curated dataset for use as a recurring face across social-media campaigns.
<table> <tr> <td><img src="./preview/serene-1.png" alt="Serene 1" width="260"/></td> <td><img src="./preview/serene-2.png" alt="Serene 2" width="260"/></td> <td><img src="./preview/serene-3.png" alt="Serene 3" width="260"/></td> </tr> <tr> <td><img src="./preview/serene-4.png" alt="Serene 4" width="260"/></td> <td><img src="./preview/serene-5.png" alt="Serene 5" width="260"/></td> <td><img src="./preview/serene-6.png" alt="Serene 6" width="260"/></td> </tr> </table>ohwx_serene
Include the trigger anywhere in your prompt. Best results when the trigger appears at the start of the prompt and the prompt clearly describes a single woman as the subject of the frame.
ohwx_serene, a portrait photograph of a young woman, soft natural light,
neutral background, looking at the camera, magazine-cover quality,
professional studio lighting on her face.
from diffusers import StableDiffusionXLPipeline
import torch
pipe = StableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
torch_dtype=torch.float16,
).to("cuda")
pipe.load_lora_weights(
"ajaynegi0079/serene-sdxl-lora",
weight_name="pytorch_lora_weights.safetensors",
)
image = pipe(
"ohwx_serene, portrait, soft studio light, magazine cover quality",
num_inference_steps=30,
guidance_scale=7.0,
).images[0]
image.save("serene.png")
The repo also ships a Replicate-compatible bundle (serene_lora_v2.tar) for use with cog-style SDXL+LoRA predictors such as fofr/sdxl-multi-controlnet-lora:
{
"prompt": "ohwx_serene, ...",
"lora_weights": "https://huggingface.co/ajaynegi0079/serene-sdxl-lora/resolve/main/serene_lora_v2.tar",
"lora_scale": 0.95,
"num_inference_steps": 30,
"scheduler": "K_EULER"
}
| Setting | Value |
|---|---|
lora_scale | 0.85 – 0.95 (0.95 dominates product context, 0.85 lets the scene breathe) |
| Inference steps | 30 |
| Guidance scale | 7.0 |
| Negative prompt | blurry, deformed, extra fingers, bad anatomy, cartoon, plastic skin, watermark, low quality, distorted face |
| Detail | Value |
|---|---|
| Base model | stabilityai/stable-diffusion-xl-base-1.0 |
| Method | LoRA (rank 8) via 🤗 PEFT |
| Resolution | 1024 × 1024 |
| Steps | 1000 |
| Final loss | ~0.017 |
| Hardware | NVIDIA T4 (Google Colab) |
pytorch_lora_weights.safetensors — raw diffusers/PEFT LoRA, for direct pipe.load_lora_weights() useserene_lora_v2.tar — Replicate cog-sdxl bundle (lora.safetensors with cog-style key names + empty embeddings.pti stub)preview/serene-1.png … preview/serene-6.png — sample images from the training datasetCC BY-NC 4.0 — non-commercial use only. For commercial / brand-ambassador licensing, contact the repo owner.