Text-to-Image
Diffusers
TensorBoard
stable-diffusion
stable-diffusion-diffusers
lora
diffusers-training
Instructions to use iamkaikai/FUI-LORA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use iamkaikai/FUI-LORA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("iamkaikai/FUI-LORA") 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 checkpoint-500/pytorch_model.bin from iamkaikai/FUI-LORA: direct link, hf CLI and curl.
- Browser
- Download file 3.29 MB
-
https://huggingface.co/iamkaikai/FUI-LORA/resolve/main/checkpoint-500/pytorch_model.bin
- Command line
-
hf download hf://iamkaikai/FUI-LORA/checkpoint-500/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/iamkaikai/FUI-LORA/resolve/main/checkpoint-500/pytorch_model.bin
3.29 MB
- Xet hash:
- 56bafbaf00672c35a9e5f9d515a586667366313886b3716cc0d13831d747ce38
- Size of remote file:
- 3.29 MB
- SHA256:
- 49d387479e256a693731158e29deae9525be9e2fa260be3a6446abdc68d382f9
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