Instructions to use adammoss/cmd_f2_d3_256_full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use adammoss/cmd_f2_d3_256_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_256_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:
- cbd8d10dd2e035afd6c9d125c18bea9e8992f588adae825c9f5043cfec38a938
- Size of remote file:
- 13.4 MB
- SHA256:
- eeae022fbd2392cd01cb02f190aeb0068b71c86f4d6062fbeef4c9a59caddff2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.