The aim of this LoRA is to essentially convert your favorite 2d furry checkpoint into a realism checkpoint without losing too much of what makes the original special. For that reason I recommend you use it almost as a slider. I used a mix of my favorite checkpoints in the sample pics above to give you an idea of what I mean as a way of showing what it looks like on different models. I wish I can say V2 is a flat upgrade over V1, but they both have there perks. Here's a summary. Feel free to test and choose what works for you. For both I still highly recommend using a face detailer. v1.0: Intentionally overtrained on a small dataset (mostly wolves and tigers) to maximize realism, but at the cost of some usability. Basically high risk, high reward. Use at 0.6 weight. Higher weights can be done but at your own risk. v2.0: Doubled the dataset size to include more species, also trained on more reasonable settings. This is the safer option but isn't as realistic as v1.0 as a result. Use-able up to 1.0 strength and beyond.v1.0 Anima: First attempt at an Anima version. Anima obviously isn't meant to be used for realistic images so don't expect pure realism just yet. The reason the lora has "Delken" in the name is because that's the AI director who's images predominantly make up the dataset. I would love to have a more varied dataset but I haven't found anyone who consistently matches the quality Delken in pure realism IMO. As of v2.0, I've started adding my own Chatgpt generated images, but I'm still more than open to suggestions. Delken if you're reading this, thanks for the awesome pics and sorry that I stole them. Feel free to DM me if you want the name taken off the lora or for anything else.

Delken Furry Realism Enhancer [Anima / Illustrious]

Trained on 269 images: { "engine": "kohya", "unetLR": 1, "clipSkip": 2, "loraType": "lora", "keepTokens": 1, "networkDim": 16, "numRepeats": 5, "resolution": 1024, "lrScheduler": "cosine", "minSnrGamma": 5, "noiseOffset": 0.1, "targetSteps": 6725, "enableBucket": true, "networkAlpha": 8, "optimizerType": "Prodigy", "textEncoderLR": 1, "maxTrainEpochs": 20, "shuffleCaption": true, "trainBatchSize": 4, "flipAugmentation": true, "lrSchedulerNumCycles": 3}

Files with SHA256: 35508493c552e724bd02209f5315f7e2ae3a175090dd71f2c377b02c0cac66fd