Text-to-Image
Diffusers
English
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
English
Instructions to use ShibaDeveloper/olivia-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShibaDeveloper/olivia-v1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ShibaDeveloper/olivia-v1.0", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "1girl, detailed, intricate, elegant, highly detailed, digital painting, artstation, concept art, matte, sharp focus, illustration, by dan mumford, yusuke murata, makoto shinkai, ross tran" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e80acb765bfe4edf39e48d8b0081d9745d672d6750b3245a4180a3fc0e6ca61f
- Size of remote file:
- 246 MB
- SHA256:
- 3cd29f0d92440e4f612217dc56fcfb7e5dcd075a702a06ce3a189b024d804339
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