Instructions to use furusu/th-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use furusu/th-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("furusu/th-diffusion", 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: openrail
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license: openrail
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tags:
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- stable-diffusion
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- text-to-image
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This model is trained from [SDv2-1](https://huggingface.co/stabilityai/stable-diffusion-2-1) for 10 epochs on 130k images and then 4 epochs on 390k images.
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