Text-to-Image
Diffusers
StableDiffusionXLPipeline
modelslab.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/dynavisionxlallinonestyli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/dynavisionxlallinonestyli 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/dynavisionxlallinonestyli", 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 text_encoder_2/pytorch_model.bin from stablediffusionapi/dynavisionxlallinonestyli: direct link, hf CLI and curl.
- Browser
- Download file 1.39 GB
-
https://huggingface.co/stablediffusionapi/dynavisionxlallinonestyli/resolve/main/text_encoder_2/pytorch_model.bin
- Command line
-
hf download hf://stablediffusionapi/dynavisionxlallinonestyli/text_encoder_2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stablediffusionapi/dynavisionxlallinonestyli/resolve/main/text_encoder_2/pytorch_model.bin
1.39 GB
- Xet hash:
- 6e753c581fed7a78fab7658123e616e73206994a5f162d5f40965cdf82a2b33f
- Size of remote file:
- 1.39 GB
- SHA256:
- fbf4b340422efba455471bac4175a6054a0dcc00ff4a522cd3f82691867c03ec
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.