Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use evanscho/davi-tests with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use evanscho/davi-tests with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("evanscho/davi-tests", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of daiton person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1205f722324edaad86f6e031375eb71d39d43cc38e4ca0f799c682368ec10cc2
- Size of remote file:
- 6.88 GB
- SHA256:
- 1d4170dfc7ad10b50abdbc3693da4e54321b6f86133db3d6d951db14ce4551c3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.