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:
- 85649e19823e063f5ecdcf043083dc9a7fc1247977e77f99d03dfa7247945204
- Size of remote file:
- 1 kB
- SHA256:
- 3cc9d529863b9458dbb9b91d10c2e89741ffa38f99dbc44be25770289ed29416
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.