Instructions to use jyp96/clock with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jyp96/clock 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/clock") prompt = "A photo of sks clock in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 04242ee8f3ded13bf75477518223ee91c8bb1e86d9f272063bf7c7a7f78e820d
- Size of remote file:
- 1 kB
- SHA256:
- 6cf34ac8dd2addc454aeb1ee4eaba3267c2841857e117be40ac2ed02cf581c9c
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