Instructions to use lambda/sd-naruto-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lambda/sd-naruto-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lambda/sd-naruto-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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README.md
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## Prompt engineering matters
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We find that prompt engineering does help produce compelling and consistent Naruto style portraits.
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For example, writing prompts such as '<person_name> ninja portrait' or '<person_name> in the style of Naruto tends to produce results that are closer to the style of Naruto character with the characteristic headband and other elements of costume.
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Here are a few examples of prompts with and without prompt engineering that will illustrate that point.
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## Prompt engineering matters
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We find that prompt engineering does help produce compelling and consistent Naruto style portraits.
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For example, writing prompts such as '<person_name> ninja portrait' or '<person_name> in the style of Naruto' tends to produce results that are closer to the style of Naruto character with the characteristic headband and other elements of costume.
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Here are a few examples of prompts with and without prompt engineering that will illustrate that point.
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