Text-to-Image
Diffusers
StableDiffusionXLPipeline
stablediffusionapi.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/dynavision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/dynavision 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/dynavision", 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 Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.bin from stablediffusionapi/dynavision: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/stablediffusionapi/dynavision/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://stablediffusionapi/dynavision/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/stablediffusionapi/dynavision/resolve/main/vae/diffusion_pytorch_model.bin
167 MB
- Xet hash:
- e305acc026a80b021edb3faeeb4022e3496cd9219823aabc5745fbb6b14955c5
- Size of remote file:
- 167 MB
- SHA256:
- a50a417f168e5e8220b74ccef4d974f8993169b4d1645d52906ba12fde188fdb
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