Instructions to use iskandre/output3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use iskandre/output3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("iskandre/output3", 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
- Xet hash:
- 3b2e8ba6163d99a0747ac904097aade4486a88b4b74ba803eead6ce4565fef4c
- Size of remote file:
- 1.72 GB
- SHA256:
- 8ba459ca07ef238e953e658fe514317150271e1df15d70d19faf04f3249cd6d5
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