Instructions to use wangjian21/KM_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/KM_8 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_8") prompt = "Kelly McKernan's style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 7629af19a882131d6ca6f9640766bb6a8c6c0460da5778cdf700f6a36c1ffec2
- Size of remote file:
- 486 kB
- SHA256:
- 62118679a22469575d857bf314b48ea381cd7626a9b6b2bfa7ea6725c2a0b62f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.