Create Textual Inversion.md
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#->`--RETARD'S GUIDE TO TEXTUAL INVERSION--`<-#
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->*Quitters never win, and winners never quit.*<-
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Textual inversion allows you to train data sets of specific styles or things, which will then be tied to a specific word. It does this without affecting how the model file works as a whole, allowing you to inject keyword shortcuts. If that doesn't excite you, let me put it another way -
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This lets you tie a keyword to specific people, things, places, or art styles in Stable Diffusion that you otherwise would be unable to directly reference. It's a game changer.
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==**If you'd prefer to run the trainer locally:**==
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You can do so using [**this repo**](https://github.com/huggingface/diffusers/tree/main/examples/textual_inversion)
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However this guide is for training on Colab, so you may have to figure out some things yourself.
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(Also local Textual Inversion requires at least 12gb of vram at a minimum)
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!!!note In the beginning...
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**NOTE: You will need Stable Diffusion installed before proceeding, follow the recommended setup guide [**HERE**](https://rentry.org/voldy)
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**STEP 1:** In file explorer, navigate to your root stable diffusion directory (`/stable-diffusion-webui`).
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Create a new folder in this location called `embeddings` (If there isn't one already)
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**STEP 2:** Visit the [Stable Diffusion Concept Library](https://huggingface.co/sd-concepts-library) and pick any model.
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After selecting the one you wish to install, open a git bash in your `/embeddings` folder and type `git clone` followed by the model URL
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eg. `git clone https://huggingface.co/sd-concepts-library/bonzi-monkey`
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**STEP 3:** Enter the directory for the model you just downloaded.
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Open `token-identifier.txt` and copy the contents, ignoring the < > (you need to enter them when you put the token into your prompt, but the file name is irrelevant to that).
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**STEP 4:** Right click on learned_embeds.bin, click rename, paste what you copied out of token-identifier.txt, and hit enter
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**STEP 5:** Move this newly renamed `.bin` file to the `/embeddings` directory. Feel free to delete the directory you cloned for the model once you have moved the `.bin` file out of it.
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**Step 6:** Launch Voldy's SD and make sure your newly added model works.
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Pay attention to the name of the `.bin`, That's the keyword which tells Stable Diffusion to use it.
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Use the name within `< >` brackets, alongside normal prompts:
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Example prompt: `<bonzi-monkey>, photorealistic, oil painting, vintage`
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==Enjoy!==
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!!!note But I want to make my own!
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**Step 1:** Once you've figured out what you want to integrate, pick 3-5 photos of your selection, and crop them down into square images, preferably **512x512**
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**Step 2:** Upload your photos to a publicly accessible database.
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[Imgur](https://imgur.com) allows for hidden photos with a publicly accessible link
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**Step 3:** Go to the [Textual Inversion Colab](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_textual_inversion_training.ipynb#scrollTo=Yl3r7A_3ASxm) and follow the step by step instructions to run the model training, clicking the play button to the left at each new portion.
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For your image files, make sure whatever you're inputting is the **direct link** ending in `.jpg`, .`png`, or something of the like.
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!!! info Make sure you have a [Huggingface](https://huggingface.co/join) account. The Colab will give you a link to generate your token code, when you follow it, generate a **write code**
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**Step 4:** Once the training has fully run, click the folder on the left side of the screen.
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Click `sd-concept-output`, click the three dots to the right of `learned_embeds.bin`, click download.
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Once the file has downloaded, rename it to whatever you provided as your placeholder token.
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**Step 5:** Move this newly renamed `.bin` file to the `/embeddings` directory.
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**Step 6:** Launch Voldy's SD and make sure your newly added model works.
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==Have fun!==
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