Instructions to use aditya11997/kandi2-decoder-3.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aditya11997/kandi2-decoder-3.2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aditya11997/kandi2-decoder-3.2", torch_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:
- df2214c2143ac52065d120c8f9141c2624844372099e1267280c823013d79413
- Size of remote file:
- 10 GB
- SHA256:
- c34992bf0403977fcbdc30c476d3aa5dcc7b2e118edab123a96253666b06021e
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