Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use KCS97/can with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KCS97/can with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KCS97/can", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks can" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- aa3ad75ecabdd24afc99f3ccda0f956f3b73d468b47b85367ce9be4715f6463f
- Size of remote file:
- 6.88 GB
- SHA256:
- b83f0df4e72106564f5e421228a619c8b73a36236f2621ab3eb90e8151b3673c
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