Instructions to use adammoss/cmd_f2_d3_128_full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use adammoss/cmd_f2_d3_128_full with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("adammoss/cmd_f2_d3_128_full", 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:
- 14222aecd72628290759b33ae69743d02f1e541f8f1e68b12279432bea935f99
- Size of remote file:
- 53.3 MB
- SHA256:
- 861cd259ded55dce9bb464e5a824cd28832c2bb43af5c1234d4bd8386f178a00
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.