Text-to-Image
Diffusers
English
Chinese
lora
template:diffusion-lora
flux
flux.1-dev
automotive-design
industrial-design
design
agent-friendly
Instructions to use XonarLabs/OLOID_Framework with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use XonarLabs/OLOID_Framework 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("XonarLabs/OLOID_Framework") prompt = "xonar_ext_SUV_rough, A professional studio photography of a SUV, silver metallic gloss paint, 8k resolution, cinematic lighting, dark grey studio background." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 0fc7160289ed7a3538fb7e4b3d8f437a0c56786dbed5906d862331397e3f63d1
- Size of remote file:
- 64 kB
- SHA256:
- 490431b0c892b814ad23e4eb6be5b3bb25d896b1126636ac2e79fc5144934ca9
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