Instructions to use Zeta-Young/sd3-lora-tsmini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Zeta-Young/sd3-lora-tsmini with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Zeta-Young/sd3-lora-tsmini") 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 pytorch_lora_weights.safetensors from Zeta-Young/sd3-lora-tsmini: direct link, hf CLI and curl.
- Browser
- Download file 18.8 MB
-
https://huggingface.co/Zeta-Young/sd3-lora-tsmini/resolve/main/pytorch_lora_weights.safetensors
- Command line
-
hf download hf://Zeta-Young/sd3-lora-tsmini/pytorch_lora_weights.safetensors
-
curl -L -o pytorch_lora_weights.safetensors https://huggingface.co/Zeta-Young/sd3-lora-tsmini/resolve/main/pytorch_lora_weights.safetensors
18.8 MB
- Xet hash:
- ce0c570e31f937e899481adb364b5bb6e0e5d27956faf66977aa8d84bd0df73c
- Size of remote file:
- 18.8 MB
- SHA256:
- e2e80e748c8ae2c3a805bc7ae8eed54dd165bf8bff9be04857c2c3ae251cdad9
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