Instructions to use arslanali900/trained-sd3-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use arslanali900/trained-sd3-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("arslanali900/trained-sd3-lora", dtype=torch.bfloat16, device_map="cuda") prompt = "A photo of sks dog in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ede7cfc266dfcfc25d55e67ff35a7aa7538d82609dcfec4a79efd791b984d390
- Size of remote file:
- 9.6 MB
- SHA256:
- b12ffd99506de14ef222136bbb880349a0b69ecd911d6e300e3732ccdcf1ad94
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