Instructions to use jyp96/dog6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jyp96/dog6 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jyp96/dog6") prompt = "A photo of sks dog6 in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- b605886b906b19d86240a4d3b60d805e3e6ac421df7f26d79d7511908fa3d9ea
- Size of remote file:
- 1.09 MB
- SHA256:
- f8c677cb9c15ebc640dd71270ba26b6035913696a7cbb710dd2f3f9cc3a0499d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.