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 Settings
- Draw Things
- DiffusionBee
Download Hyper-SD3-8steps-CFG-lora.safetensors from ByteDance/Hyper-SD: direct link, hf CLI and curl.
- Browser
- Download file 472 MB
-
https://huggingface.co/ByteDance/Hyper-SD/resolve/main/Hyper-SD3-8steps-CFG-lora.safetensors
- Command line
-
hf download hf://ByteDance/Hyper-SD/Hyper-SD3-8steps-CFG-lora.safetensors
-
curl -L -o Hyper-SD3-8steps-CFG-lora.safetensors https://huggingface.co/ByteDance/Hyper-SD/resolve/main/Hyper-SD3-8steps-CFG-lora.safetensors
472 MB
- Xet hash:
- fc25aa990aaf29e099f436f1a720c15ef303efde5c7312205705a41feaf1d96a
- Size of remote file:
- 472 MB
- SHA256:
- fc6a3e73e14ed11e21e4820e960d7befcffe7e333850ada9545f239e9aa6027e
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