Instructions to use Metal079/SonicDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Metal079/SonicDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Metal079/SonicDiffusion", 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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3 Dreambooth models based on AnythingV3 for the base model and training images from Evan Stanley's twitter.
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evan5400 was trained on ~30 images for 5400 steps, use keyword 'sonic person' when prompting
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UPDATE: V2 is released as is much better, would recommend using instead https://huggingface.co/Metal079/SonicDiffusionV2
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3 Dreambooth models based on AnythingV3 for the base model and training images from Evan Stanley's twitter.
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evan5400 was trained on ~30 images for 5400 steps, use keyword 'sonic person' when prompting
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