Instructions to use iriscope/oscavatar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use iriscope/oscavatar with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("iriscope/oscavatar", dtype=torch.bfloat16, device_map="cuda") prompt = "oscavatar" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 156edfd1d739b2377ec1f6ef347e309ad0b5f682eb1d67b224f0ee3d0ccd72f2
- Size of remote file:
- 492 MB
- SHA256:
- 5f9a1e23fb9cc35a64fd89783b7a0bc89a9f399dcd05a1f12a7d5cc74738e5b9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.