Instructions to use dataautogpt3/Proteus-RunDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dataautogpt3/Proteus-RunDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dataautogpt3/Proteus-RunDiffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "score_9, Side View of a Roman Warrior pierced By a spear, cinimatic " image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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README.md
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Distinct from Pony's Unet
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For legal and ethical considerations, it is important to clarify that ProteusV0.4-RunDiffusion does not incorporate any Unet components originally developed by Pony. Our model’s innovative capabilities and improvements are the result of proprietary advancements and do not infringe upon Pony’s original Unet architecture.
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Distinct from Pony's Unet
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For legal and ethical considerations, it is important to clarify that ProteusV0.4-RunDiffusion does not incorporate any Unet components originally developed by Pony. Our model’s innovative capabilities and improvements are the result of proprietary advancements and do not infringe upon Pony’s original Unet architecture.
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There will be a upcoming Human Preference Study and Research Publication
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