Instructions to use blanchon/nitro_e_1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use blanchon/nitro_e_1024 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_1024", 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:
- adbfcd878a1742ee02efca9bb4a5dc080ed9d71460073b96c4eb2a0dd31db6b8
- Size of remote file:
- 625 MB
- SHA256:
- 124bbf5ed3c731b41243c49141480c92b3428d132d3bdfa690c8a1d92b45f16c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.