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 Settings
- Draw Things
- DiffusionBee
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In partnership with RunDiffusion.com, we proudly present ProteusV0.4, an evolutionary step forward in AI-generated art. This model marks the first successful retraining and merging of the acclaimed Pony Diffusion v6 XL CLIP model, enhancing both tag capabilities and artistic representation without sacrificing character recognition.
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Key Features:
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## Introducing ProteusV0.4: A Breakthrough in AI Collaboration
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In partnership with RunDiffusion.com, we proudly present ProteusV0.4, an evolutionary step forward in AI-generated art. This model marks the first successful retraining and merging of the acclaimed Pony Diffusion v6 XL CLIP model, enhancing both tag capabilities and artistic representation without sacrificing character recognition.
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Key Features:
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