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Running
on
Zero
| ## Usage | |
| Enter a prompt and click `Generate`. Roll the `🎲` for a random prompt. | |
| ### Prompting | |
| Positive and negative prompts are embedded by [Compel](https://github.com/damian0815/compel) for weighting. See [syntax features](https://github.com/damian0815/compel/blob/main/doc/syntax.md) to learn more and read [Civitai](https://civitai.com)'s guide on [prompting](https://education.civitai.com/civitais-prompt-crafting-guide-part-1-basics/) for best practices. | |
| #### Arrays | |
| Arrays allow you to generate different images from a single prompt. For example, `[[cat,corgi]]` will expand into 2 separate prompts. Make sure `Images` is set accordingly (e.g., 2). Only works for the positive prompt. Inspired by [Fooocus](https://github.com/lllyasviel/Fooocus/pull/1503). | |
| ### Embeddings | |
| Select multiple negative [textual inversion](https://huggingface.co/docs/diffusers/en/using-diffusers/textual_inversion_inference) embeddings. Fast Negative and Bad Dream can be used standalone or together; Unrealistic Dream should be combined with one of the others: | |
| * [`<fast_negative>`](https://civitai.com/models/71961/fast-negative-embedding-fastnegativev2): all-purpose (default) | |
| * [`<bad_dream>`](https://civitai.com/models/72437?modelVersionId=77169): DreamShaper-style | |
| * [`<unrealistic_dream>`](https://civitai.com/models/72437?modelVersionId=77173): realistic add-on | |
| ### Styles | |
| Styles are prompt templates from twri's [sdxl_prompt_styler](https://github.com/twri/sdxl_prompt_styler) Comfy node. Start with a subject like "cat", pick a style, and iterate from there. | |
| ### Scale | |
| Rescale up to 4x using [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN) from [ai-forever](ai-forever/Real-ESRGAN). | |
| ### Models | |
| Each model checkpoint has a different aesthetic: | |
| * [cyberdelia/CyberRealistic_v5](https://huggingface.co/cyberdelia/CyberRealistic): photorealistic | |
| * [Lykon/dreamshaper-8](https://huggingface.co/Lykon/dreamshaper-8): general purpose (default) | |
| * [fluently/Fluently-v4](https://huggingface.co/fluently/Fluently-v4): general purpose | |
| * [Linaqruf/anything-v3-1](https://huggingface.co/Linaqruf/anything-v3-1): anime | |
| * [prompthero/openjourney-v4](https://huggingface.co/prompthero/openjourney-v4): Midjourney-like | |
| * [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5): base | |
| * [SG161222/Realistic_Vision_v5.1](https://huggingface.co/SG161222/Realistic_Vision_V5.1_noVAE): photorealistic | |
| * [XpucT/Deliberate_v6](https://huggingface.co/XpucT/Deliberate): general purpose | |
| ### Image-to-Image | |
| The `🖼️ Image` tab enables the image-to-image and IP-Adapter pipelines. Either use the image input or select a generation from the gallery. To disable, simply clear the image input (the `x` overlay button). | |
| Denoising strength is essentially how much the generation will differ from the input image. A value of `0` will be identical to the original, while `1` will be a completely new image. You may want to also increase the number of inference steps. Only applies to the image-to-image input. | |
| ### IP-Adapter | |
| In an image-to-image pipeline, the input image is used as the initial latent. With [IP-Adapter](https://github.com/tencent-ailab/IP-Adapter), the input image is processed by a separate image encoder and the encoded features are used as conditioning along with the text prompt. | |
| For capturing faces, enable `IP-Adapter Face` to use the full-face model. You should use an input image that is mostly a face and it should be high quality. You can generate fake portraits with Realistic Vision to experiment. Note that you'll never get true identity preservation without an advanced pipeline like [InstantID](https://github.com/instantX-research/InstantID), which combines many techniques. | |
| ### Advanced | |
| #### DeepCache | |
| [DeepCache](https://github.com/horseee/DeepCache) caches lower UNet layers and reuses them every `Interval` steps. Trade quality for speed: | |
| * `1`: no caching (default) | |
| * `2`: more quality | |
| * `3`: balanced | |
| * `4`: more speed | |
| #### FreeU | |
| [FreeU](https://github.com/ChenyangSi/FreeU) re-weights the contributions sourced from the UNet’s skip connections and backbone feature maps. Can sometimes improve image quality. | |
| #### Clip Skip | |
| When enabled, the last CLIP layer is skipped. Can sometimes improve image quality. | |
| #### Tiny VAE | |
| Enable [madebyollin/taesd](https://github.com/madebyollin/taesd) for near-instant latent decoding with a minor loss in detail. Useful for development. | |