Instructions to use SD-Next/MicroDecoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SD-Next/MicroDecoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SD-Next/MicroDecoder", 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
Update README.md
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README.md
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license: apache-2.0
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pipeline_tag: text-to-image
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library_name: diffusers
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---
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# MicroDecoder
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Train ββββββββββββββββββββ 400/400 100% 0:00:00 0:06:33 Train(psnr=21.029 ssim=0.640 lpips=2.784 l1=0.089 lab=0.156 grad=0.073 sat=0.124 fft=0.071 total=4.536) Validate(psnr=30.607 ssim=0.927 lpips=1.242 l1=0.020 lab=0.046 grad=0.046 sat=0.057 fft=0.032 total=1.964)
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Complete: Time=393.89 Epoch/Sec=1.02 PSNR=30.61 dB @ Epoch=400
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Save: filename="microdecoder-minimaxh3.safetensors"
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```
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license: apache-2.0
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pipeline_tag: text-to-image
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library_name: diffusers
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tags:
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- vae
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---
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# MicroDecoder
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Train ββββββββββββββββββββ 400/400 100% 0:00:00 0:06:33 Train(psnr=21.029 ssim=0.640 lpips=2.784 l1=0.089 lab=0.156 grad=0.073 sat=0.124 fft=0.071 total=4.536) Validate(psnr=30.607 ssim=0.927 lpips=1.242 l1=0.020 lab=0.046 grad=0.046 sat=0.057 fft=0.032 total=1.964)
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Complete: Time=393.89 Epoch/Sec=1.02 PSNR=30.61 dB @ Epoch=400
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Save: filename="microdecoder-minimaxh3.safetensors"
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```
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