Instructions to use AlexanderLab/ozdrs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlexanderLab/ozdrs 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("AlexanderLab/ozdrs") prompt = "ozdrs" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 509d60e6d54fc0c9854a36702602fc1836d7e25c8fc08cb11a72b4197ef80816
- Size of remote file:
- 344 MB
- SHA256:
- 0b12ec0cdf4fdc9de7178b265af18dca3c19f26cc71b91e504b12c91fd04db2b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.