Rename to usage

README.md

@@ -46,7 +46,7 @@ Gradio-based Stable Diffusion 1.5 app on ZeroGPU.
 
 ## Usage
 
-See [`info.md`](https://huggingface.co/spaces/adamelliotfields/diffusion/blob/main/info.md).
+See [`usage.md`](https://huggingface.co/spaces/adamelliotfields/diffusion/blob/main/usage.md).
 
 ## Installation
 

app.py

@@ -218,8 +218,8 @@ with gr.Blocks(
                             scale=3,
                         )
 
-            with gr.TabItem("ℹ️ Info"):
-                gr.Markdown(read_file("info.md"), elem_classes=["markdown"])
+            with gr.TabItem("ℹ️ Usage"):
+                gr.Markdown(read_file("usage.md"), elem_classes=["markdown"])
 
     with gr.Group():
         output_images = gr.Gallery(

info.md → usage.md

@@ -1,47 +1,49 @@
 ## Usage
 
-Enter a prompt and click `Generate`. Read [Civitai](https://civitai.com)'s guide on [prompting](https://education.civitai.com/civitais-prompt-crafting-guide-part-1-basics/) to learn more.
+Enter a prompt and click `Generate`.
 
-### Compel
+### Prompting
 
-Positive and negative prompts are embedded by [Compel](https://github.com/damian0815/compel), enabling weighting and blending. See [syntax features](https://github.com/damian0815/compel/blob/main/doc/syntax.md).
+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`
 
-### Embeddings
+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.
 
-Textual inversion embeddings are installed for use in the `Negative` prompt.
+#### Negative Prompt
 
-* [Bad Prompt](https://civitai.com/models/55700/badprompt-negative-embedding): `<bad_prompt>`
-* [Negative Hand](https://civitai.com/models/56519/negativehand-negative-embedding): `<negative_hand>`
-* [Fast Negative](https://civitai.com/models/71961/fast-negative-embedding-fastnegativev2): `<fast_negative>`
-  - includes Negative Hand
-* [Bad Dream](https://civitai.com/models/72437?modelVersionId=77169): `<bad_dream>`
-* [Unrealistic Dream](https://civitai.com/models/72437?modelVersionId=77173): `<unrealistic_dream>`
-  - pair with Fast Negative and the Realistic Vision model
+Start with a [textual inversion](https://huggingface.co/docs/diffusers/en/using-diffusers/textual_inversion_inference) embedding:
 
-### Arrays
+* [`<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)
 
-Arrays allow you to generate different images from a single prompt. For example, `a cute [[cat,corgi,koala]]` will expand into 3 prompts. For this to work, you first have to increase `Images`. Note that it only works for the positive prompt. Inspired by [Fooocus](https://github.com/lllyasviel/Fooocus/pull/1503).
+And iterate from there. You can use weighting in the negative prompt as well.
 
-### Autoincrement
+#### Arrays
 
-If `Autoincrement` checked, the seed will be incremented for each image in range `Images`. When using arrays, you might want this disabled so the same seed is used.
+Arrays allow you to generate different images from a single prompt. For example, `man, [[blue,blue+,blue++]] eyes` will expand into 3 separate prompts. Make sure `Images` is set accordingly (e.g., 3). Only works for the positive prompt. Inspired by [Fooocus](https://github.com/lllyasviel/Fooocus/pull/1503).
 
-## Models
+When using arrays, you should disable `Autoincrement` so the same seed is used for each generation.
 
-All use `float16` (or `bfloat16` if supported).
+### Models
 
-* [fluently/fluently-v4](https://huggingface.co/fluently/Fluently-v4)
-* [linaqruf/anything-v3-1](https://huggingface.co/linaqruf/anything-v3-1)
-* [lykon/dreamshaper-8](https://huggingface.co/Lykon/dreamshaper-8)
-* [prompthero/openjourney-v4](https://huggingface.co/prompthero/openjourney-v4)
-* [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5)
-* [sg161222/realistic_vision_v5.1](https://huggingface.co/SG161222/Realistic_Vision_V5.1_noVAE)
+* [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
+#### Schedulers
 
-All are based on [k_diffusion](https://github.com/crowsonkb/k-diffusion) except [DEIS](https://github.com/qsh-zh/deis) and [DPM++](https://github.com/LuChengTHU/dpm-solver). Optionally, the [Karras](https://arxiv.org/abs/2206.00364) noise schedule can be used.
+All are based on [k_diffusion](https://github.com/crowsonkb/k-diffusion) except [DEIS](https://github.com/qsh-zh/deis) and [DPM++](https://github.com/LuChengTHU/dpm-solver). 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)
+* [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)
@@ -49,24 +51,32 @@ All are based on [k_diffusion](https://github.com/crowsonkb/k-diffusion) except
 * [LMS](https://huggingface.co/docs/diffusers/api/schedulers/lms_discrete)
 * [PNDM](https://huggingface.co/docs/diffusers/api/schedulers/pndm)
 
-## Advanced
+### Advanced
 
-### DeepCache
+#### DeepCache
 
-[DeepCache](https://github.com/horseee/DeepCache) (Ma et al. 2023) caches UNet layers determined by `Branch` and reuses them every `Interval` steps. Leaving `Branch` on **0** caches lower layers, which provides a greater speedup. An `Interval` of **3** is the best balance between speed and quality; **1** means no cache.
+[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
+#### T-GATE
 
-[T-GATE](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. Works well with DeepCache.
+[T-GATE](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. Defaults to `20`.
 
-### Tiny VAE
+#### ToME
 
-Enable [madebyollin/taesd](https://github.com/madebyollin/taesd) for almost instant latent decoding with a minor loss in detail. Useful for development and ideation.
+[ToMe](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.
 
-### Clip Skip
+#### Tiny VAE
 
-When enabled, the last CLIP layer is skipped. This can improve image quality and is commonly used with anime models.
+Enable [madebyollin/taesd](https://github.com/madebyollin/taesd) for almost instant latent decoding with a minor loss in detail. Useful for development.
 
-### Prompt Truncation
+#### 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.