Instructions to use wangjian21/KM_500e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/KM_500e with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("wangjian21/KM_500e") prompt = "Kelly McKernan's style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 88334c1df6f18ed76607f8f66863a7df901dfb8618ea9d0def64f26dc718d6f6
- Size of remote file:
- 6.59 MB
- SHA256:
- dcfb72206cd77aa6548c449b00b343bc5b74c2e4c12d4f553fee9ac0f1d8936d
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