Text-to-Image
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StableDiffusionPipeline
open-diffusion
od-v2
openskyml
Instructions to use openskyml/open-diffusion-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use openskyml/open-diffusion-v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("openskyml/open-diffusion-v2", 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 openskyml/open-diffusion-v2: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/openskyml/open-diffusion-v2/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://openskyml/open-diffusion-v2/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/openskyml/open-diffusion-v2/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- e6171ffb6dfe6cc99d74709755691b241411a512357aa775a4639062aeb9716f
- Size of remote file:
- 335 MB
- SHA256:
- eac6df9beeebd0106fa4600ef1d15454ce83cb7853870ab3dd45ec89542838ab
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