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 Settings
- Draw Things
- DiffusionBee
Commit ·
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Parent(s): 91634a7
Update README.md
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README.md
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inference: true
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widget:
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- text: >-
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1girl, beautiful girl, face, yellow eyes,
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example_title: example 1girl
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---
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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prompt = "1girl, beautiful girl, face, yellow eyes,
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image = pipe(prompt).images[0]
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image.save("./olivia_img.png")
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inference: true
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widget:
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- text: >-
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1girl, beautiful girl, face, yellow eyes, black hair
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example_title: example 1girl
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---
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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prompt = "1girl, beautiful girl, face, yellow eyes, black hair"
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image = pipe(prompt).images[0]
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image.save("./olivia_img.png")
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