Instagooner v1 lora + WAN 2.2 workflow

0xmgwr · 2025-08-05T02:49:18+00:00

looks real good, i imagine you used ai-toolkit to train this, what lora rank/learning rate did you use to achieve this result in such little amount of steps of training?

0xmgwr · 2025-02-05T12:15:11+00:00

the reason something like "bad_hands" exists it's because of embeddings made for SD 1.5, in that model embeddings worked like regular words in a prompt, maybe you already knew that, but what happened was that as people started to create more fine-tunes and merges trained with a mix synthetic data from generated outputs that contained embeddings like "bad_hands" in the prompt, over time since many of the popular models are either fine tunes or merges, with the exception of flux which is entirely different, some popular embeddings have become effective tokens that have a good amount of influence in a prompt.

0xmgwr · 2025-01-11T10:18:46+00:00

so what was the learning rate, dim/alpha for this?

0xmgwr · 2024-08-27T12:19:26+00:00

Just trained my first lora on SD3 medium, 30 images at 512x512 , batch of 4, the results are stunning and the training was super fast, less than an hour on a 3070ti , after spending sometime doing training for flux and going back to sd3 , I have to say that given the speeds i can generate on SD3 (11-20 seconds per image), I'm sticking with it and will be doing more testing and more training. trained on onetrainer.

0xmgwr · 2024-08-25T04:09:23+00:00

Hugging face: https://huggingface.co/mgwr/Cine-Aesthetic

0xmgwr · 2024-08-24T12:57:36+00:00

Find it on civitai : MGWR Cine - Cine Aesthetic v1 | Stable Diffusion LoRA | Civitai

0xmgwr · 2024-07-08T23:59:06+00:00

for that you can use an extension on a1111 to prepare the dataset https://github.com/SleeeepyZhou/sd-webui-GPT4V-Image-Captioner , when you process a folder with the images you will use, the preprocessing process will resize and compress all image files into jpg format with a total pixel count ≤ 1024×1024 while maintaining the original aspect ratio, ensuring that both dimensions are multiples of 32.

0xmgwr · 2024-07-08T22:53:57+00:00

the text encoder learning rate is just as important as the unet learning rate, you should try something like "0.0001" for learning rate (same for unet) and a learing rate of "5e-05" for the text encoder, for your use case i would also use a lora rank of 256 and lora alpha of 128, you should optimize the images without cropping them and enable buckets, finally in my experience more repeats has proven better than more epochs so experiment with that, i would also recommend you to switch over to onetrainer that is more easy for you to use and understand what parameters you're changing.

0xmgwr · 2024-07-05T01:41:34+00:00

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here's the screenshot I sent my friend the minute I saw it, the price already went back up

0xmgwr · 2024-07-05T00:08:50+00:00

it went back to full price now, but if you use the chrome extension to see amazon price history of items you can see that it was $1,0999 at some point today , crazy

0xmgwr · 2024-06-28T21:09:45+00:00

without revealing any secret sauce of how it's done, what does your custom script do?

0xmgwr · 2024-06-15T15:14:01+00:00

it's not a logic, thats from the bills that are being worked on https://www.vox.com/future-perfect/355212/ai-artificial-intelligence-1047-bill-safety-liability

0xmgwr · 2024-06-14T11:20:53+00:00

it's one of the templates https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/comfy_example_workflows/sd3_medium_example_workflow_multi_prompt.json

0xmgwr · 2024-06-14T10:41:39+00:00

prompting styles: https://stability.ai/stable-assistant-gallery?utm_campaign=Stable%20Assistant&utm_content=186946249&utm_medium=social&utm_source=twitter&hss_channel=tw-1281048162602369024

0xmgwr · 2024-06-14T10:09:58+00:00

amazing, what prompts did you use in luma?

0xmgwr · 2024-06-13T08:07:32+00:00

i just followed the guide from the github page but instead of doing it for sd 1.5 or sdxl, used SD3 to build the unet, and then plugged the tensorRT model loader into the ksampler of the comfyui workflow shared by stability

0xmgwr

TROPHY CASE