Instructions to use naclbit/trinart_characters_19.2m_stable_diffusion_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use naclbit/trinart_characters_19.2m_stable_diffusion_v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("naclbit/trinart_characters_19.2m_stable_diffusion_v1", 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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license: creativeml-openrail-m
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## Stable Diffusion TrinArt Characters model v1
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trinart_characters_19.2m_stable_diffusion_v1 is a stable diffusion v1-based model trained by roughly 19.2M anime/manga style images (pre-rolled augmented images included) plus final finetuning by about 50,000 images. This model seeks for a sweet spot between artistic style versatility and anatomical quality within the given model spec of SDv1.
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license: creativeml-openrail-m
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## Note
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A newer version of this model has been released:
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https://huggingface.co/naclbit/trinart_derrida_characters_v2_stable_diffusion
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## Stable Diffusion TrinArt Characters model v1
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trinart_characters_19.2m_stable_diffusion_v1 is a stable diffusion v1-based model trained by roughly 19.2M anime/manga style images (pre-rolled augmented images included) plus final finetuning by about 50,000 images. This model seeks for a sweet spot between artistic style versatility and anatomical quality within the given model spec of SDv1.
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