Instructions to use mlgawd/dev_nsf4_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mlgawd/dev_nsf4_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("mlgawd/dev_nsf4_2", 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
- Xet hash:
- d27cef143f0bc80e287d04ebf31ccb638e14aa74391a9596ab366fb48ee60c0d
- Size of remote file:
- 6.69 GB
- SHA256:
- 7d76a6798709860ebc35c7c782849611ddb0e10afd6b22b07fcd1abdbd7d6c8b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.