# akegarasu/lora-scripts

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6,059 stars · 695 forks · Python · AGPL-3.0

## Links

- GitHub: https://github.com/Akegarasu/lora-scripts
- awesome-repositories: https://awesome-repositories.com/repository/akegarasu-lora-scripts.md

## Topics

`dreambooth` `finetune` `lora` `stable-diffusion`

## Description

lora-scripts is a fine-tuning toolkit designed for adapting base diffusion models to specific styles or subjects. It provides a specialized set of scripts and tools for executing low-rank adaptation and Dreambooth training jobs.

The project features a web-based graphical interface that manages the training workflow, allowing users to configure and execute jobs without manual script editing. This interface maps user inputs to hyperparameters and provides a real-time dashboard for monitoring training metrics and loss curves to track model convergence.

The system includes a dataset tagging manager for organizing and editing image labels. To ensure consistent execution across different hardware hosts, the training environment is provided as a pre-configured containerized setup.

## Tags

### Artificial Intelligence & ML

- [Custom Stable Diffusion Training](https://awesome-repositories.com/f/artificial-intelligence-ml/custom-stable-diffusion-training.md) — Provides a complete workflow for training custom Stable Diffusion models to recognize specific entities or styles.
- [LoRA Fine-Tuning Tools](https://awesome-repositories.com/f/artificial-intelligence-ml/full-parameter-fine-tuning/custom-data-fine-tunings/lora-fine-tuning-tools.md) — Ships a comprehensive set of scripts and tools for low-rank adaptation (LoRA) of diffusion models.
- [Diffusion Model Training](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/diffusion-visual-models/generative-ai-models/diffusion-models/diffusion-model-training.md) — Implements specialized fine-tuning logic for diffusion models via standalone Python scripts.
- [Diffusion Model LoRA Fine-Tuning](https://awesome-repositories.com/f/artificial-intelligence-ml/language-model-fine-tuning/partial-layer-fine-tunings/diffusion-model-lora-fine-tuning.md) — Provides a web interface for configuring and executing LoRA and Dreambooth fine-tuning jobs for diffusion models.
- [Model Training Management Interfaces](https://awesome-repositories.com/f/artificial-intelligence-ml/model-training-management-interfaces.md) — Features a web-based dashboard for configuring hyperparameters and triggering training runs without manual scripting. ([source](https://github.com/Akegarasu/lora-scripts/blob/main/README.md))
- [Automated Image Tagging](https://awesome-repositories.com/f/artificial-intelligence-ml/image-classification/image-level-tagging/automated-image-tagging.md) — Automates the labeling of image datasets using specialized vision models and editing tools. ([source](https://github.com/Akegarasu/lora-scripts/blob/main/README.md))
- [Automated Processing Pipelines](https://awesome-repositories.com/f/artificial-intelligence-ml/image-classification/image-level-tagging/automated-image-tagging/automated-processing-pipelines.md) — Provides an automated pipeline to process raw images and generate structured metadata labels for model training.
- [Dataset Tagging Managers](https://awesome-repositories.com/f/artificial-intelligence-ml/image-classification/image-level-tagging/dataset-tagging-managers.md) — Includes a dedicated tagging manager for organizing and editing image labels used in training.
- [Image Classification Datasets](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/machine-learning-datasets/image-classification-datasets.md) — Organizes and structures image datasets with labels for training image recognition and generation models.
- [Model Training Monitoring](https://awesome-repositories.com/f/artificial-intelligence-ml/model-training-monitoring.md) — Tracks and visualizes model convergence and loss curves in real time to monitor training quality.
- [Dataset Labeling Interfaces](https://awesome-repositories.com/f/artificial-intelligence-ml/reinforcement-learning-training/robot-policy-trainers/imitation-and-reinforcement-learning-toolkits/dataset-labeling-interfaces.md) — Provides integrated tools for tagging and editing dataset labels to improve training accuracy. ([source](https://github.com/Akegarasu/lora-scripts/blob/main/README-zh.md))
- [Training Progress Monitors](https://awesome-repositories.com/f/artificial-intelligence-ml/training-progress-monitors.md) — Provides a real-time dashboard for visualizing training metrics and loss curves to track model convergence. ([source](https://github.com/akegarasu/lora-scripts#readme))

### Development Tools & Productivity

- [Web-Based Command Interfaces](https://awesome-repositories.com/f/development-tools-productivity/shell-command-execution/web-based-command-interfaces.md) — Translates user inputs from a graphical dashboard into command-line arguments for training scripts.

### Data & Databases

- [Item Tagging and Organization](https://awesome-repositories.com/f/data-databases/tag-based-search/item-tagging-and-organization.md) — Includes built-in editors and automated processes for organizing and managing image tags in datasets. ([source](https://github.com/akegarasu/lora-scripts#readme))

### System Administration & Monitoring

- [Real-Time Metric Visualization](https://awesome-repositories.com/f/system-administration-monitoring/real-time-metric-visualization.md) — Features a web dashboard that renders live convergence curves by polling training logs and loss data.