Text-to-Image
Diffusers
StableDiffusionPipeline
stablediffusionapi.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/dvarch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/dvarch with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/dvarch", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 0eabe4d19b9a1c06d8b0097b48021e5f3a71217094140fbc400a3b688f77de84
- Size of remote file:
- 492 MB
- SHA256:
- 2a7b00e9119d053a06b86b14a49af46ac7fc7db78fbe1dc832b735b00834083a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.