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QGO - PromptingReal - v1
QGO-10b-fix (fixed CLIP)
QGO-10a
mk8
Bonus: ??? dreambooth
QGO-10b
QGO - PromptingReal

QGO - PromptingReal

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#fotorrealista
#anatomical
#analog
#Modelo Base
#model
#¿Dónde, tío?
#polvo cinematográfico
#Hombres
#Fotografía
#Realismo
#semirrealista
#fotorrealista
#????
#analog
#Fotografía
#Realismo

Hello world

Let's get real

It's been a while since the last update, and this iteration is quite different than the last. That's not to say it is necessarily groundbreaking compared to anything else on this website (it's a merge after all), but I've tried to focus on a couple of very specific things:

  1. A high amount of realism without any use of LoRAs or embeddings.

    Having a good basis provides a lot of room to go crazy with those later.

  2. Functional with a limited/small negative prompt.

    Similarly, a small negative prompt often makes for the most realistic outputs. It is always possible to write your novel, or add embeddings in there along the way.

  3. Consistency in poses / hands / other features within these constraints.

  4. Decent control over light and darkness through prompt alone

    There are great LoRAs out there for lighting / noise offset, but there is already some great functionality by default.

  5. Responsiveness to the wildest lists of wildcards ChatGPT has to offer.

    I like to have random lists of locations, time periods, clothing/materials, concepts, all generated (and embellished) by your local GPT.

Recommended VAE (not included): vae-ft-mse-840000-ema-pruned

-High base resolutions are advised: such as 640x896 for a portrait format

-If possible use hires.fix or a similar implementation: a denoise of 0.3~0.5 will do well in most situations various ESRGAN upscalers give good results. x1_ITF_SkinDiffDetail_Lite_v1 is the one used in all examples here, but there are other great options.

-Don't feel obligated to use time consuming samplers such as the one in most examples. I was suffering from a short bout of SDE Karras addiction when generating the examples, but I have since come back to 2M Karras @ 15~20 steps, which is usually my baseline and more than fine on its own (even with hires.fix).

*Note that some of the example prompts can generate ??????, prompt against this to prevent it. For actual examples of ?????? you can check out the album uploaded separately.

**The model in the metadata is QGO-3002a, which is the same as QGO-PromptingReal-v1

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QEGo
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2023-03-20
Publicar modelo
2023-05-31
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Detalles del modelo
Tipo
Checkpoint
Fecha de lanzamiento
2023-05-31
Modelo básico
SD 1.5
Introducción de versión

It's been a while since the last update, and this iteration is quite different than the last. That's not to say it is necessarily groundbreaking compared to anything else on this website (it's a merge after all), but I've tried to focus on a couple of very specific things:

  1. A high amount of realism without any use of LoRAs or embeddings.

    Having a good basis provides a lot of room to go crazy with those later.

  2. Functional with a limited/small negative prompt.

    Similarly, a small negative prompt often makes for the most realistic outputs. There is always room to write your novel, or add embeddings in there later.

  3. Consistency in poses / hands / other features within these constraints.

  4. Responsiveness to the wildest lists of wildcards ChatGPT has to offer.

    I like to have random lists of locations, time periods, clothing/materials, concepts, all generated (and embellished) by your local GPT.

Recommended VAE (not included): vae-ft-mse-840000-ema-pruned

*Note that some of the example prompts can generate ??????, prompt against this to prevent it. For actual examples of ?????? you can check out the album uploaded separately.

**The model in the metadata is QGO-3002a, which is the same as QGO-PromptingReal-v1

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Fuente: civitai

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