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
upload SDXL loras
Browse files
Hyper-SDXL-1step-lora.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c912df184c5116792d2c604d26c6bc2aa916685f4a793755255cda1c43a3c78a
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size 787359648
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Hyper-SDXL-2steps-lora.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:69b25c0187ced301c3603c599c0bc509ac99b8ac34db89a2aecc3d5f77a35187
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size 787359648
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Hyper-SDXL-4steps-lora.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:12f81a27d00a751a40d68fd15597091896c5a90f3bd632fb6c475607cbdad76e
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size 787359648
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Hyper-SDXL-8steps-lora.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ca689190e8c46038550384b5675488526cfe5a40d35f82b27acb75c100f417c1
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size 787359648
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