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---
license: mit
base_model: OnomaAIResearch/Illustrious-xl-early-release-v0
tags:
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
- text-to-image
- diffusers
- lora
- gradients-on-demand
inference: true
---
# LoRA Model for Illustrious-xl-early-release-v0
This is a LoRA (Low-Rank Adaptation) model trained on custom dataset.
## Model Details
- **Base Model**: OnomaAIResearch/Illustrious-xl-early-release-v0
- **LoRA Rank**: 128
- **LoRA Alpha**: 128
- **Training Framework**: Kohya SS
- **Precision**: bfloat16
## Training Configuration
- **Learning Rate**: 2e-5
- **Batch Size**: 8
- **Epochs**: 50
- **Optimizer**: AdamW8Bit
- **LR Scheduler**: Cosine with Restarts
- **Resolution**: 1024x1024
## Usage
You can use this LoRA with any SDXL-compatible interface:
### With Diffusers
```python
from diffusers import DiffusionPipeline
import torch
# Load base model
pipe = DiffusionPipeline.from_pretrained(
"OnomaAIResearch/Illustrious-xl-early-release-v0",
torch_dtype=torch.float16,
variant="fp16",
use_safetensors=True
)
pipe.to("cuda")
# Load LoRA weights
pipe.load_lora_weights("dada22231/ba2b5d89-3688-448e-9197-d9fd377c4f5a")
# Generate image
prompt = "your prompt here, lora style"
image = pipe(
prompt,
num_inference_steps=20,
guidance_scale=7.5,
).images[0]
```
### With ComfyUI
1. Download the .safetensors file
2. Place it in `ComfyUI/models/loras/`
3. Use the "Load LoRA" node in your workflow
### With Automatic1111
1. Download the .safetensors file
2. Place it in `stable-diffusion-webui/models/Lora/`
3. Use `<lora:ba2b5d89-3688-448e-9197-d9fd377c4f5a:1>` in your prompt
## Training Data
This model was trained on a custom dataset as part of the Gradients on Demand subnet.
## License
This model is licensed under the MIT License.
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