Instructions to use CabalResearch/Mugen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CabalResearch/Mugen with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CabalResearch/Mugen", 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
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README.md
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It has been trained for 7 additional epochs, totalling under **8000$** for a full latent space conversion, while preserving and improving upon model anime knowledge.
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In particular, we have paid attention to
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Overall, model performs particularly well with textures and patterns that were previously simply impossible due to SDXL VAE. We prioritized keeping our training as standard-friendly as possible, so local community can easily train on it like on a new Base Model, which it practically is.
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It has been trained for 7 additional epochs, totalling under **8000$** for a full latent space conversion, while preserving and improving upon model anime knowledge.
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In particular, we have paid attention to characters in this iteration, and developed in-house approach for benchmarking their performance, about which you can read below.
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Overall, model performs particularly well with textures and patterns that were previously simply impossible due to SDXL VAE. We prioritized keeping our training as standard-friendly as possible, so local community can easily train on it like on a new Base Model, which it practically is.
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