Instructions to use ShinnosukeU/parameter_v25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShinnosukeU/parameter_v25 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ShinnosukeU/parameter_v25", 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:
- 54e0f5ab29d15a87404d1ce33b36f5d65bb8991ef19536320cbea50604da87e3
- Size of remote file:
- 492 MB
- SHA256:
- 9e1d64d7f4d775014678d921f1e967cbf8725e746c9ba2cb496bd9835f11492c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.