SDv1.5 Patterns1K LoRA Usage Guide
Introduction
SDv1.5 Patterns1K LoRA
is a fine-tuned model based on Stable Diffusion v1.5, specifically optimized for generating patterns from the Patterns-1K dataset. 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 Patterns-1K dataset. You can download the trained LoRA weights from the following links:
- LoRA weights after 1 epoch: 1epoch_lora.safetensors
- LoRA weights after 100 epochs: 100epoch_lora.safetensors
3. Test the Model
After downloading the weights, you can use the test_lora.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 test_lora.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 1 epoch: 1epoch_test_results.png
Results after 100 epochs: 100epoch_test_results.png
Here are the example results: