Instructions to use iriscope/oscarvatar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use iriscope/oscarvatar 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/oscarvatar", 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 iriscope/oscarvatar: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/iriscope/oscarvatar/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://iriscope/oscarvatar/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/iriscope/oscarvatar/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 67ad1e8f422510b5bbdfde91b3a228c922653fa517992fbf0311c47bcccd1ba7
- Size of remote file:
- 246 MB
- SHA256:
- 24336970c3fbd1e26de3e829012f5456c9a1ba238bc35a0bd5bb23fec59ecd3f
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