Does everything a PonyXL model can, but "nearly" photorealistic!
V4 update, improved faces and lighting trained in.
Workflow I use to create the preview images sdxlpony-face-and-upscale-civitai-metadata
What it does:
If you're familiar with Pony models, they are very specific in their prompting and subject focus. I made this model to work the same way, but get closer to photorealistic. It uses the same prompting and LoRAs that other PonyXL models use.
What it doesn't do:
It's not a general model. Like other PonyXL models, it's more designed to work with booru tags and mostly does images with people in them. If you want to make general images, use a standard SDXL model.
What's coming:
PonyXL is trained on images with "exaggerated" anatomy. So I've purposely kept it from getting too photorealistic for the moment due to uncanny valley issues. As I train it more, I'll bring it closer to photoreal. In the meantime, use prompts such as (realistic photograph, depth of field, bokeh, etc) to help get the photo look.
How to use:
I recommend using the standard SDXL VAE. CFG should range from 7 to 10, higher than other models. You can experiment with different samplers. I prefer DPM++ 2S a Karras for consistency and DPM++ 3M SDE Exponential to get wild. Prompting for quality should use the score system like other PonyXL models. (score_9, score_8_up, score_7_up) in the positive prompt and (score_3_up, score_4_up, score_5_up) in the negative prompt. Otherwise your images will be very plain.
Alternately, you can use the Pony PDXL embeddings that I created for much easier use.
Description
FAQ
Comments (14)
Under "How to use:" you say to use [score_3_up, score_4_up, score_5_up] in the negative prompt. My understanding is that the correct tags should be [score_3, score_4, score_5] since the *_up is meant to encompass a range of scores instead of just the specific ones. v6 of Pony was accidentally skewed to need the whole score system due to an error that wasn't caught while it was being trained, and technically it's likely that having *_up or not has little to no effect.
that info comes from the pony creator on the technical info on their discord, if that updated, use whatever the current meta is
@xCirusX If you have source for this updated information it would be much appreciated.
Anything to drop the score tags lol.
@Zovya I could be wrong. I was just basing it off the way I read what was written, since score_8 is considered a separate tag from score_8_up. But like I mentioned it's really hard to tell if there is a significant effect, even after testing.
@xCirusX Interesting, why did you specify only the negative prompt, when '_up' is in the positive prompt as well?
@olivereaduzuh From what the original author had wanted. having the *_up was meant to be used as a lower baseline to be used for inference. Meaning score_6_up, would include score_6 thru score_9, allowing you to only have to use a single tag instead of using them all together as we currently have been told to do. Having *_up in the negative prompt could potentially mean that score_4_up would include score_4 thru score_9.
@xCirusX Oh I understand now, I didn't realize the ordering of the Scores was so delicate. Thanks Cirus
Huge improvement over v1. Well done!
Amazing model! Faces are way better then V1. Thanks!
So where is the zPDXLrl and its negative counterpart? The only ones available at the embedding model page are zPDXL,zPDXLpg and zPDXLxxx. Was working on making them proper safetensors since you only uploaded pickletensors of those when I saw the previews here lacking that one
This latest version (v2) is probably the best "realistic" Pony model that currently exists. It can also do quick renders when set to 12 steps @ 2.5CFG on DPM2++2M SDE SGMUniform. If there's one criticism it's that it doesn't accept any Pony style LoRAs but that's completely fine with me as there are other checkpoints I can use for those. Exceptional work!
thanks for the kind comment. I use pony loras with this all the time, works great. some style loras may conflict with the photorealistic nature, but everything else should work
can we train loras on this?
should be able to, as with any model
Details
Files
everclearPNYByZovya_v2VAE.safetensors
Mirrors
everclearPNYByZovya_v2VAE.safetensors
everclearPNYByZovya_v2VAE.safetensors
everclearPNYByZovya_v2VAE.safetensors
everclearPNYByZovya_v2VAE.safetensors
everclearPNYByZovya_v2VAE.safetensors
everclearPNYByZovya_v2VAE.safetensors
test.safetensors
everclearPNYByZovya_v2.safetensors
everclearPNYByZovya_v2VAE.safetensors
test.safetensors
everclearPNYByZovya_v2VAE.safetensors
everclearPNYByZovya_v2VAE.safetensors
everclearPNYByZovya_v2VAE.safetensors
everclearPNYByZovya_v2VAE.safetensors
Available On (2 platforms)
Same model published on other platforms. May have additional downloads or version variants.







