Text-to-Image
Diffusers
TensorBoard
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
textual_inversion
Instructions to use dxli/clock with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dxli/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("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_textual_inversion("dxli/clock") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- dae2b9c11da7fdd8e5538e85a207eb6867e15e7bb9145110161c85345cf7f83a
- Size of remote file:
- 1.22 GB
- SHA256:
- 16d28f2b37109f222cdc33620fdd262102ac32112be0352a7f77e9614b35a394
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