Instructions to use prithivMLmods/Seamless-Pattern-Design-Flux-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prithivMLmods/Seamless-Pattern-Design-Flux-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("prithivMLmods/Seamless-Pattern-Design-Flux-LoRA") prompt = "This is a vibrant digital illustration featuring a seamless pattern of four Chihuahua heads, each adorned with large, bright pink sunglasses. The dogs have tan fur with white chests and expressive, wide eyes. The background is a solid, vivid blue, interspersed with scattered pink heart shapes, adding a playful and whimsical touch. The illustration style is cartoonish, with smooth shading and exaggerated features, creating a cheerful and eye-catching design." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 8921f5295d13e7da8a68bae13ece03ee9324c1f7ebca1071c81344c7c89100ff
- Size of remote file:
- 613 MB
- SHA256:
- d417cf4a2f45e871152f0b8b4854e915098524fd054fecf5ab9b13f7e6401d8a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.