Instructions to use nevproject/SonicDiffusionV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nevproject/SonicDiffusionV2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nevproject/SonicDiffusionV2", 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 Settings
- Draw Things
- DiffusionBee
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README.md
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- stabilityai/stable-diffusion-xl-base-1.0
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pipeline_tag: text-to-image
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library_name: diffusers
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---
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SonicDiffusionV2.ckpt was trained on AnythingV3 for 200 epochs of 203 hand captioned images from various artists.
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Much more customizable in style and context from previous version
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- stabilityai/stable-diffusion-xl-base-1.0
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pipeline_tag: text-to-image
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library_name: diffusers
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license: openrail
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tags:
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- art
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- sonic
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---
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SonicDiffusionV2.ckpt was trained on AnythingV3 for 200 epochs of 203 hand captioned images from various artists.
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Much more customizable in style and context from previous version
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