Instructions to use dosesnrolls1/lexlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dosesnrolls1/lexlora 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("dosesnrolls1/lexlora") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
.webp)
- Xet hash:
- 6c326b0355c4274a4d67b0ea5c14337f02f301197d1d4e0bb109ccf6d17e045b
- Size of remote file:
- 39.9 kB
- SHA256:
- 3ebeac5567f286d64d894d37f6d7d9d59dd434ba2894edbbc53efe1b82b1d338
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.