Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use XGGNet/ckpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use XGGNet/ckpt with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("XGGNet/ckpt", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- c2eedefd47f45ef7cac507153a6ba2eaa8b5d3523dd3130be5231b67784bb98d
- Size of remote file:
- 6.88 GB
- SHA256:
- 0e965d2e0107d179f1b7928238b832d58128e96746b127828c3596850f08a34c
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