Tag: AI
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TBD Experiment: Multiple Classifications
Hypothesis: Dreambooth can utilize multiple classifications in regularization to improve model training while maintaining model style and data. Each classification should correspond to a tag that is common throughout the training data.
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Experiment: High Accuracy Training
Utilizing Kohya_ss GUI I’m experimenting with various settings sourced from different tutorials in the hopes of gathering a basic configuration that can generate accurate renders while using as little time and VRAM as possible during training. Methodology: 1.) To quickly iterate through configurations I’m using a small dataset of 5 images, all with captions, to…
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Dreambooth Kohya SS Install
– Github Above is the repository for Kohya SS Dreambooth, to install simply clone the repository to a separate folder using Git then run the install.bat file. Note: For better training speed ( iterations per second ) using RTX 40xx GPU’s it’s advised to use CUDA 11.8 so that Xformers can properly access the newest…
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Note: How to turn any model into an inpainting model
– Reddit Possible merging technique to enable inpainting on various models. May have implications for other types of merges.
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Resource: Dreambooth Training README
– Github README describing proper methods for constructing a dataset. According to the README Regularization images allow for prior preservation of a models existing dataset.
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Resource: Training Stable Diffusion with Dreambooth
–Blog Post This article describes experiments with different Learning Rates in training models using Dreambooth. FTA: Summary of Initial Results To get good results training Stable Diffusion with Dreambooth, it’s important to tune the learning rate and training steps for your dataset. Faces are harder to train. In our experiments, a learning rate of 2e-6…
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Stable Diffusion Experiments
AI module experiments