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", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 8c79b77fbd560df12d83536d5f682fc49c8f9f0a38ab632c0a25066c01bd4c78
- Size of remote file:
- 3.44 GB
- SHA256:
- 64468ad9dcfe9e48a32e91b4f379c02e99f378b2dcd2c4899c6c4ff9350fa5f2
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