Text-to-Image
Diffusers
TensorBoard
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
Instructions to use CSAle/DilbertDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CSAle/DilbertDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CSAle/DilbertDiffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "dilbert walking his dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- b581c101bfaf57da173f527ed2cf0d7afc1f7debf03d9f867045851d3c8dd7d1
- Size of remote file:
- 3.44 GB
- SHA256:
- c3f4a3b236c627cb322b51100cf428114056765eb415af982f1bb6829df6c74c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.