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Running
on
Zero
| ## Usage | |
| Enter a prompt and click `Generate`. | |
| ### Prompting | |
| Positive and negative prompts are embedded by [Compel](https://github.com/damian0815/compel) for weighting. You can use a float or +/-. For example: | |
| * `man, portrait, blue+ eyes, close-up` | |
| * `man, portrait, (blue)1.1 eyes, close-up` | |
| * `man, portrait, (blue eyes)-, close-up` | |
| * `man, portrait, (blue eyes)0.9, close-up` | |
| Note that `++` is `1.1^2` (and so on). 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. | |
| #### Negative Prompt | |
| Start with a [textual inversion](https://huggingface.co/docs/diffusers/en/using-diffusers/textual_inversion_inference) embedding: | |
| * [`<bad_prompt>`](https://civitai.com/models/55700/badprompt-negative-embedding) | |
| * [`<negative_hand>`](https://civitai.com/models/56519/negativehand-negative-embedding) | |
| * [`<fast_negative>`](https://civitai.com/models/71961/fast-negative-embedding-fastnegativev2) | |
| * [`<bad_dream>`](https://civitai.com/models/72437?modelVersionId=77169) | |
| * [`<unrealistic_dream>`](https://civitai.com/models/72437?modelVersionId=77173) | |
| And add to it. You can use weighting in the negative prompt as well. | |
| #### 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). | |
| ### 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. | |
| ### Models | |
| Each model checkpoint has a different aesthetic: | |
| * [lykon/dreamshaper-8](https://huggingface.co/Lykon/dreamshaper-8): general purpose (default) | |
| * [fluently/fluently-v4](https://huggingface.co/fluently/Fluently-v4): general purpose merge | |
| * [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 | |
| #### Schedulers | |
| Optionally, the [Karras](https://arxiv.org/abs/2206.00364) noise schedule can be used: | |
| * [DEIS 2M](https://huggingface.co/docs/diffusers/en/api/schedulers/deis) (default) | |
| * [DPM++ 2M](https://huggingface.co/docs/diffusers/en/api/schedulers/multistep_dpm_solver) | |
| * [DPM2 a](https://huggingface.co/docs/diffusers/api/schedulers/dpm_discrete_ancestral) | |
| * [Euler a](https://huggingface.co/docs/diffusers/en/api/schedulers/euler_ancestral) | |
| * [Heun](https://huggingface.co/docs/diffusers/api/schedulers/heun) | |
| * [LMS](https://huggingface.co/docs/diffusers/api/schedulers/lms_discrete) | |
| * [PNDM](https://huggingface.co/docs/diffusers/api/schedulers/pndm) | |
| ### Advanced | |
| #### DeepCache | |
| [DeepCache](https://github.com/horseee/DeepCache) (Ma et al. 2023) caches lower UNet layers and reuses them every `Interval` steps: | |
| * `1`: no caching | |
| * `2`: more quality (default) | |
| * `3`: balanced | |
| * `4`: more speed | |
| #### T-GATE | |
| [Temporal gating](https://github.com/HaozheLiu-ST/T-GATE) (Zhang et al. 2024) caches self and cross attention computations up to `Step`. Afterwards, attention is no longer computed and the cache is used, resulting in a noticeable speedup. | |
| #### ToMe | |
| [Token merging](https://arxiv.org/abs/2303.17604) (Bolya & Hoffman 2023) reduces the number of tokens processed by the model. Set `Ratio` to the desired reduction factor. ToMe's impact is more noticeable on larger images. | |
| #### Tiny VAE | |
| Enable [madebyollin/taesd](https://github.com/madebyollin/taesd) for almost instant latent decoding with a minor loss in detail. Useful for development. | |
| #### Clip Skip | |
| When enabled, the last CLIP layer is skipped. This _can_ improve image quality with anime models. | |
| #### Prompt Truncation | |
| When enabled, prompts will be truncated to CLIP's limit of 77 tokens. By default this is _disabled_, so Compel will chunk prompts into segments rather than cutting them off. | |