Instructions to use dfsdfsdfsd/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dfsdfsdfsd/test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dfsdfsdfsd/test", 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:
- 5d4be9c6521eb8c71a62b7889db6cf14a835f8a551485526be3c2a0fc06f23bb
- Size of remote file:
- 12.6 GB
- SHA256:
- 7a300761db87a96756cdf72ac9c3f653776d10c08fe430be9ac3e6de23498caa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.