Instructions to use blanchon/nitro_e_512_lite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use blanchon/nitro_e_512_lite with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("blanchon/nitro_e_512_lite", 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:
- 385b8240f2b26444a14d19f46c04dccffb39ddc11e41b0facf1863199688ff17
- Size of remote file:
- 842 MB
- SHA256:
- eb2d01aaeb801e50295e2777415723eefce6c5726e0d1d9a77890e89fe155a21
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