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Introduction to #StableDiffusion #TextualInversion Embeddings
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Which commit of the #Automatic1111 Web UI we are using and how to checkout / switch to specific commit of any Git project
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Used command line arguments of Automatic1111 webui-user.bat file
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Automatic1111 command line arguments
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How to and where to put Stable Diffusion models and VAE files in Automatic1111 installation
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Why do we use latest VAE file and what does VAE file do
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Training settings of Automatic1111
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All about names of text embeddings
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What is initialization text of textual inversion training
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Embedding inspector extension of Automatic1111
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How to set number of vectors per token when doing Textual Inversion training
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Technical and detailed explanation of tokens and their numerical weights vectors in Stable Diffusion
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How the prompts getting tokenized - turned into tokens - by using tokenizer extension
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Setting number of training vectors
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Where embedding files are saved in automatic1111 installation
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All about preprocess images before TI training
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Training tab of textual inversion
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What to and how to set embedding learning rate
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What are the Batch size and Gradient accumulation steps and how to set them
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How to set training learning rate according to Batch size and Gradient accumulation steps
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What are prompt templates, what are they used for, how to set and use them in textual inversion training
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What are filewords and how they are used in training in automatic1111 web ui
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How to edit image captions when doing textual inversion training
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From training images pool, how and why did i choose some of them and not all of them
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Why I did add noise to the backgrounds of some training dataset images
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How should be your training dataset. What is a good training dataset
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Save TI training checkpoints
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Which latent sampling method is best
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Training started
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Overclock GPU to get 10% training speed up
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Where to find TI training preview images
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Where to see used final prompts during training
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How to use inspect_embedding_training script to determine overtraining of textual inversion
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What is training loss
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Technical difference of Textual Inversion, DreamBooth, LoRA and HyperNetworks training
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Over 200 epochs and already got very good sample preview images
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How to set newest VAE file as default in the settings of automatic1111 web ui
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How to use generated embeddings checkpoint files
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How to test different checkpoints via X/Y plot and embedding files name generator script
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How to upscale image by using AI
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How to use multiple embeddings in a prompt
Description:
Learn the intricacies of Stable Diffusion Textual Inversion (TI) and Text Embeddings using the Automatic1111 Web UI in this comprehensive tutorial video. Explore topics such as setting up the Automatic1111 environment, understanding command line arguments, managing Stable Diffusion models and VAE files, and configuring training settings. Dive deep into the technical aspects of tokens, vectors, and embedding learning rates. Discover how to prepare and preprocess training datasets, use prompt templates, and leverage filewords for effective training. Gain insights into monitoring training progress, avoiding overtraining, and comparing different AI training techniques. Master the use of generated embeddings, test various checkpoints, and learn how to upscale images using AI. By the end of this tutorial, you'll have a thorough understanding of Textual Inversion and its application in Stable Diffusion image generation.

How to Do Stable Diffusion Textual Inversion - Text Embeddings by Automatic1111 Web UI Tutorial

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Introduction to #StableDiffusion #TextualInversion Embeddings