Instructions to use martineux/renderkid3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use martineux/renderkid3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("martineux/renderkid3", 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
- Draw Things
- DiffusionBee
- Xet hash:
- b422d2389fb5031bd15b44befc4b029acd177dd489cfb5ebe21dcc3c8aa5e6f5
- Size of remote file:
- 167 MB
- SHA256:
- 1c689d249c0ee43e5d4956bbe6c2cb0819a924e1c0e9118c5e8e3504b3bc363c
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