Instructions to use jyp96/dog3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jyp96/dog3 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jyp96/dog3") prompt = "A photo of sks dog3 in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 43fb7c5ae04801ca35d9304fc272bf48cb53c81f85d3ee1e47e3c8401e56f26e
- Size of remote file:
- 1.55 MB
- SHA256:
- 48c2a8e96ad871390133436c11c1757b69af2e335f21c00ce4f230702d2ad3f8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.