Instructions to use gokaygokay/Flux-Seamless-Texture-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gokaygokay/Flux-Seamless-Texture-LoRA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("gokaygokay/Flux-Seamless-Texture-LoRA") prompt = "smlstxtr, A pattern of crystalline formations in amethyst purple, seamless texture" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Size of the dataset?
Thank you for making this public, could I ask you about the size of the dataset you used for finetuning?
15 images
thank you for such a quick answer and even more for providing examples, I was thinking whether I can train model to generate seamless pattern that could be repeated and when I have seen you LORA I thought that it is supposed to achieve that.
But then looking more closely the results aren't seamless. But seeing the dataset it's no surprise :) Because many of the images are not seamless.
Thank you nonetheless!
This is tiling test, i think what would be cool is you can try to cherry pick good ones and train another lora with good examples from this LoRA.
Maybe you didnt zoom to examples that is why you think they are not seamless. Huggingface shows them square but my examples are 1024x768 thats why you might think they are not seamless.
This is tiling test, i think what would be cool is you can try to cherry pick good ones and train another lora with good examples from this LoRA.
Yes but I was thinking about more complex pattern at least like the snowflakes you have in results, I will try during next week probably...
Yes, i also recommend using good captions. It is really easy to make it for 15 images with hand, you dont need autocaptioner vlms. They would be more accurate and rich.
"smlstxtr, A close-up view of lava with various shades of orange and black, seamless texture"
"smlstxtr, A blue surface with square indentations and screws, seamless texture"
My captions were like this they are not that much descriptive

















