Instructions to use Outrun32/sd-miyazaki-model-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Outrun32/sd-miyazaki-model-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("Outrun32/sd-miyazaki-model-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-5000/optimizer.bin from Outrun32/sd-miyazaki-model-lora: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/Outrun32/sd-miyazaki-model-lora/resolve/main/checkpoint-5000/optimizer.bin
- Command line
-
hf download hf://Outrun32/sd-miyazaki-model-lora/checkpoint-5000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Outrun32/sd-miyazaki-model-lora/resolve/main/checkpoint-5000/optimizer.bin
6.59 MB
- Xet hash:
- 012467ed089a59cdc1b47a46306547a7f74994916ee7ce583c1101604ca0c275
- Size of remote file:
- 6.59 MB
- SHA256:
- d2766db1bf0791d30a32721b41f2fba44fb9e3ea0f34c7f42c9624aad1571b87
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