Automate the process of training a LORA model on your images using DreamBooth with ease! This README will guide you through the setup and usage of this project.
Access your Colab notebook for training a LORA model:
Access your Colab notebook for generating images using an old LORA file:
This project allows you to train a LORA model on your images using the DreamBooth AI tool with minimal effort. By following the steps outlined in this README, you can quickly set up and start the training process.
Follow these steps to get started with AutoTrain DreamBooth:
Place the images you want to use for training in the images/ folder. Make sure your images are appropriately labeled and organized for the best results.
Create a unique and specific prompt that describes the task or concept you want the LORA model to learn. The quality of your prompt will greatly affect the output of your trained model, so make it as precise as possible.
Find "DreamCapture_Studio_bot" on Telegram by visiting this link and start a chat with the bot.
The bot will reply with the target_user_id. You'll need this user ID to interact with the bot programmatically.
Execute the code cells in Colab by using Runtime > Run all or individual cells in your Colab environment. This will initiate the training process using your images and the defined prompt.
If you encounter any issues or have questions, feel free to open an issue on this GitHub repository. We welcome any feedback or suggestions to improve this project.
Contributions are welcome! If you have ideas for enhancements or bug fixes, please fork this repository, make your changes, and submit a pull request. We appreciate your help in making this project better.
This project is licensed under the MIT License. Feel free to use and modify it for your needs.
Enjoy using AutoTrain DreamBooth and have fun experimenting with AI-based image training! 📷🤖
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