license: mit
SDv1.5 Artifacts-500 LoRA Usage Guide
Introduction
SDv1.5 Artifacts-500 LoRA is a fine-tuned model based on Stable Diffusion v1.5, specifically optimized for generating patterns from the artifacts-500 dataset(artifacts-500.zip). Using LoRA (Low-Rank Adaptation) technology, the model has been adapted to produce higher-quality patterns relevant to the dataset.
Usage Instructions
1. Download Stable Diffusion v1.5 Weights
Before you begin, ensure you have downloaded the pre-trained weights for Stable Diffusion v1.5. You can download the weights from the official Stable Diffusion repository.
2. Prepare LoRA Weights
We have trained LoRA weights for the Artifacts-500 dataset. You can download the trained LoRA weights from the following links:
- LoRA weights after 100 epochs: artifacts_100epoch_lora.safetensors
3. Test the Model
After downloading the weights, you can use the generate.py script to test the model's performance. Follow these steps:
Install Dependencies
Ensure you have the following Python libraries installed:
pip install diffusers transformers torch
4. Run the Test Script
To test the model with the LoRA weights trained for 1 epoch:
python generate.py
The param lcm_speedup decide use lcm speed up or not.
View the Results
The generated images will be saved to the specified paths:
Results after 100 epochs: 100epoch_test_results.png
Here are the example results:
