Instructions to use satsune/Osage-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use satsune/Osage-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("satsune/Osage-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 text_encoder/pytorch_model.bin from satsune/Osage-v2: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/satsune/Osage-v2/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://satsune/Osage-v2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/satsune/Osage-v2/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- c1482f3db00973ae30a45b694f2144a3224b0dbad63a7c5bc3dcec3bd9c88129
- Size of remote file:
- 492 MB
- SHA256:
- 69930a7a4c05a1f616c0d565fc06169329e7f9bae521fddab147e32ad1b9862c
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