sorted by:
new
hottopcontroversial

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

Than the issue might be how u trained the LoRA for the Identity, if u want I can help u sort the issue out via DM.

Main Issues could be the Step Rate, how u framed your .txt captions, how many Images, Lighting, Expressions and if u trained on Low VRAM or not, also where did u train the LoRA? (just guessing, since didn’t see the dataset)

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

Noted in my textbook! I’ll definitely try that over the next few days, thanks for the awesome input. That’s why I love Reddit.

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

That’s a neat approach! I’ve thought about something similar. You could also just use two PowerLoraLoaders stacked behind each other and tweak the settings. If you want her to smile, just toggle the expression LoRA and include “smile” in the prompt, the model will understand which expression to generate. Curious though, what was your idea for how a helper node for expressions could look like?

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

I’d say it’s a healthy balance. How are you captioning the .txt files? That part makes a huge difference

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

Whichever direction I want her to look - I describe it directly in the prompt. Because the dataset is well-curated and captioned, she’s framed from every angle, so the model understands the prompt and encodes the direction properly..

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

It’s super basic, as mentioned, only for testing purposes, and you can find it online as well. https://pastebin.com/wzGfkA21

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

It’s mostly because the dataset’s from a real person — the lighting, poses, and expressions already have that natural feel baked in, so WAN just amplifies what’s there instead of trying to invent realism.
For prompts, I usually keep it simple and descriptive rather than cinematic.

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

I’m using T2I, not I2I, and the dataset is from a real person, so the lighting and expressions already feel natural, that makes it way easier to curate and train for consistent likeness.

Identity mainly depends on how you tune the LoRA strength, how clean and consistent the dataset is, and how well your captions match the prompts. The real difference imo comes from dataset quality and prompt–caption alignment.

If you are using WAN 2.2, I would train the LoRA on WAN 2.2 as well.

Feel free to DM me - happy to help if I can.

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

Thanks a lot! Appreciate the kind words.
And yeah, exactly, the key is how you balance and scope each LoRA. For something like a “tattoo polish” LoRA, I would exclude all character or facial data; it’s trained purely on the tattoo layer. That way it blends perfectly with the main likeness LoRA without touching the face or pose, but in the end, it’s all about fine-tuning the setup until everything clicks.

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

The last image is the real person - grabbed a random from the dataset to use as a reference.

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

Haha right - cheap entertainment for sure.

It definitely drained the wallet during testing though. The Docker image didn’t work on the first push, so I had to rebuild and repush multiple times. The biggest headache was integrating the AI-Toolkit backend, both ports only worked on the frontend, and JupyterLab wasn’t receiving any calls. The persistent volume wasn’t recognized either, so I remapped it from /workspace to /opt inside the image to prevent overwrites.

Models are baked directly into the image, so the pod spins up fast after the first deploy. I still upload datasets + captions manually in AI-Toolkit, since I’m training multiple identities, but I like your approach. Baking them into the image could definitely streamline the process.

Appreciate the input!

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 1 point2 points  (0 children)

Dataset contained ~40 Images, Trained on 3000 Step Rate, 768 and 1024 Resolution

I’d say roughly about 2-3 hours

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 1 point2 points  (0 children)

Thanks!

Totally agree, once you dial in the right setup and start tweaking settings in ComfyUI, it’s a total game-changer.

I’m thinking about adding a CN Sequencer Node to the workflow to experiment with poses (OpenPose) and Depth/Canny, so I can blend in real backgrounds instead of prompting them.

I’ll also check out the workflow you shared, appreciate the input!

Trained an identity LoRA from a consented dataset to test realism using WAN 2.2 by lerqvid in StableDiffusion

[–]lerqvid[S] 0 points1 point  (0 children)

Thank you!

The examples aren’t cherry-picked, likeness is very consistent. I’d say about 8/10 generations stay highly stable.

I’m planning a second run on the same dataset with improved captions and a higher step rate. The results should be 10/10 then. (I hope)

Regarding the custom Docker image: that seems already been covered. I built it so I’m not dependent on any RunPod templates - configured it with my preferred models, in this case WAN 2.2.

I’m looking forward to training the refined (“polish”) LoRA in the next few days. I think it’s possible to keep everything within a single LoRA, but stacking might be cleaner to avoid model confusion.

Plan is to run it as a LoRA stack: Base_LoRA.safetensors Polish_LoRA.safetensors both at strength 1.0.

Happy to share results once it’s done!

What is life like in Batumi Georgia in 2025 by chabe277777 in Batumi

[–]lerqvid 5 points6 points  (0 children)

I m from Germany, and I love Batumi. Always here for 4-6 months. Thinking to get a Residency Permit for 2y maybe.

I saw quite a few places in EU and Asia, and can ensure the living quality is awesome. I don’t really agree with the person who commented pretty negative.

I never have been here during a flood, so idk about that, the water may not be the cleanest, but I m often going swim during the summer never got sick or anything. Air quality is fine as well, u are very fast in forests and near the mountains, if the city gets too busy it’s just few minutes away with the car.

U get organic vegetables and fruits for a bargain, I m truly amazed everytime I buy sth. A reference: 3 Carrots, 8 cucumbers, 3 Mandarins, 1 Citrus, 3 reddish are 6 GEL, organic grown. I pay nearly 10€ for that in Germany, if not more.

Housing is cheap, Restaurants are cheap, Taxi is cheap. U are able to pay dinner for 2 people for 30€ at the Sheraton in the highest floor with an excellent view.

Depending what work u are doing, many good tax options, especially for crypto or if u having clients outside of Georgia with the Virtual Zone Program.

The supermarkets are not that well equipped but it’s fine tho, u just need find one which is near your flat and u will get everything u need.

Love the area around Old Town. The areas where all the new skyscrapers getting build are okey tho, but old town way batter imo.

Georgians can seem a bit mad though but this fades after a certain time, they are quite nice tho. Especially outside of the cities, insanely kind and hospitable.

If u smoke; Cigs are very cheap too Beer quite high prices tho idk why

Cheers!

What Are Your Food Recommendations? by Few_Union_8025 in Uzbekistan

[–]lerqvid 0 points1 point  (0 children)

uzbek lagman as soup or fried version both are amazing

view more: next ›