A LoRA adapter for SDXL that generates realistic handwritten signatures from a name prompt. Trained on a cleaned/processed signature dataset with text prompts; intended for research & non-commercial use.
Usage (Diffusers)
import torch
from diffusers import DiffusionPipeline, EulerAncestralDiscreteScheduler
base = "stabilityai/stable-diffusion-xl-base-1.0"
lora = "sl4shuur/sdxl-handwriting-signaturegen-lora" # this repo id
pipe = DiffusionPipeline.from_pretrained(base, torch_dtype=torch.float16, use_safetensors=True).to("cuda")
pipe.load_lora_weights(lora)
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
negative = "extra words, extra text, blurry, artifacts, extra lines, scribble, low quality, gray/black background, double signature"
name = "B. Navya"
prompt = f"signaturegen style: handwritten name {name} on white background"
image = pipe(
prompt=prompt,
negative_prompt=negative,
num_inference_steps=50,
guidance_scale=7.0,
height=512, width=512,
generator=torch.Generator(device='cuda').manual_seed(42)
).images[0]
image.save("sample.png")
Weights for this model are available in Safetensors format.
Prompting tips
- Use a clear name inside the prompt.
- Keep it single-line vs multi-line if that’s what you trained on.
- Recommended: 50 steps, guidance 6.5–8.0, seed fixed for reproducibility.
Trigger words
You should use signaturegen style: to trigger the image generation.
Files
pytorch_lora_weights.safetensors
— LoRA adapter weights.
Training & Data
- Base model:
stabilityai/stable-diffusion-xl-base-1.0
- Dataset:
sl4shuur/handwriting-signatures-dataset
- Preprocessing: cleaning, cropping, centering, resize to 256×256; manual curation.
Training script
!accelerate launch /content/diffusers/examples/text_to_image/train_text_to_image_lora_sdxl.py \
--pretrained_model_name_or_path="stabilityai/stable-diffusion-xl-base-1.0" \
--train_data_dir="sl4shuur/handwriting-signatures-dataset" \
--caption_column="text" \
--resolution=256 \
--mixed_precision="fp16" \
--allow_tf32 \
--gradient_checkpointing \
--use_8bit_adam \
--enable_xformers_memory_efficient_attention \
--dataloader_num_workers=4 \
--learning_rate=1e-4 --lr_scheduler="cosine" --lr_warmup_steps=0 \
--rank=4 \
--max_train_steps=2000 \
--checkpointing_steps=500 \
--train_batch_size=2 --gradient_accumulation_steps=4 \
--seed=69 \
--output_dir="/content/drive/Shareddrives/SignatureGenDataset/lora_signature_model_OUT" \
--hub_model_id="sl4shuur/sdxl-handwriting-signaturegen-lora" \
--push_to_hub
Intended use & limitations
- Research / non-commercial.
- Generates stylized signatures from names; not for identity verification or impersonation.
- Can fail on very long names or non-Latin scripts (out-of-distribution).
- See original Stable Diffusion XL Base 1.0 page for additional limitations and biases.
License
CC-BY-NC-4.0
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Model tree for sl4shuur/sdxl-handwriting-signaturegen-lora
Base model
stabilityai/stable-diffusion-xl-base-1.0