Instructions to use satsune/Osage-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use satsune/Osage-v3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("satsune/Osage-v3", 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/pytorch_model.bin from satsune/Osage-v3: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/satsune/Osage-v3/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://satsune/Osage-v3/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/satsune/Osage-v3/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 0bfa22228999193909f2127dbf06e2f46a8cf0411a61c49fefa3a3bb9d6e5147
- Size of remote file:
- 492 MB
- SHA256:
- b3026342e95f795dcd8ea3e3b7d9fad934c9ae60943a8b35c2f8719c6c5053bc
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