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
Download microdecoder-minimaxh3.safetensors from SD-Next/MicroDecoder: direct link, hf CLI and curl.
- Browser
- Download file 9.71 MB
-
https://huggingface.co/SD-Next/MicroDecoder/resolve/main/microdecoder-minimaxh3.safetensors
- Command line
-
hf download hf://SD-Next/MicroDecoder/microdecoder-minimaxh3.safetensors
-
curl -L -o microdecoder-minimaxh3.safetensors https://huggingface.co/SD-Next/MicroDecoder/resolve/main/microdecoder-minimaxh3.safetensors
9.71 MB
- Xet hash:
- f6a6d4c54a0077446b8b09209d4d8e0aaae4bae947bb0d2c00042206457ff25b
- Size of remote file:
- 9.71 MB
- SHA256:
- eb9427a1d8f92bdd123feda388f9865738095689df0a395eb49956bcd3b0415d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.