Instructions to use diffusers/lora-trained-xl-keramer-face with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/lora-trained-xl-keramer-face with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/stable-diffusion-xl-base-0.9", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("diffusers/lora-trained-xl-keramer-face") prompt = "a photo of sks person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/scheduler.bin from diffusers/lora-trained-xl-keramer-face: direct link, hf CLI and curl.
- Browser
- Download file 563 Bytes
-
https://huggingface.co/diffusers/lora-trained-xl-keramer-face/resolve/main/checkpoint-500/scheduler.bin
- Command line
-
hf download hf://diffusers/lora-trained-xl-keramer-face/checkpoint-500/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/diffusers/lora-trained-xl-keramer-face/resolve/main/checkpoint-500/scheduler.bin
563 Bytes
- Xet hash:
- 8fdff6df3c742cc2b577f37d1cb8d7902e6e9a2c557434a84786a1ebc7f4ab46
- Size of remote file:
- 563 Bytes
- SHA256:
- 62783ff6f0ae2c2ccc177b097e430c03940c5e70c38a191df273c5cf7ab1227c
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