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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- c326d5050cf304198c9f4152887c5490dc2ff8218364396e811daee57f305056
- Size of remote file:
- 19.1 MB
- SHA256:
- 7f99fe9b35c6bbb958946c809061b68b506f5530da61f86326db187cd8f1b088
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