Instructions to use ByteDance/Hyper-SD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ByteDance/Hyper-SD with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ByteDance/Hyper-SD") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Add generated example
Browse filesGenerated example for model ByteDance/Hyper-SD.
Prompt: a heart made of water in a mossy forest scene
- README.md +5 -0
- images/example_vqf89s77d.png +0 -0
README.md
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- stable-diffusion
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- flux
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base_model: black-forest-labs/FLUX.1-dev
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---
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# Hyper-SD
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- stable-diffusion
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- flux
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base_model: black-forest-labs/FLUX.1-dev
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widget:
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- text: a heart made of water in a mossy forest scene
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output:
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url: images/example_vqf89s77d.png
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---
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# Hyper-SD
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images/example_vqf89s77d.png
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