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
- Draw Things
- DiffusionBee

- Xet hash:
- 43c5c38dacd77a5c7394d2dd2c0b88e8974d0b63d0c209e7e48f75af2e5fb7f3
- Size of remote file:
- 3.82 MB
- SHA256:
- 08fe61b73d8976b7b64faf0fcc66f36ffadcae601fb8f5ebed788017c4565a90
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