Instructions to use varb15/TemporalNet2-stable-diffusion-2-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use varb15/TemporalNet2-stable-diffusion-2-1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("varb15/TemporalNet2-stable-diffusion-2-1", 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:
- 690bde25a4d96dc99b8cf87284d0d80df82689de7a38e8459d0a1d2edd2bdd73
- Size of remote file:
- 1.46 GB
- SHA256:
- 0ed9deaaf54e1d4438017d6db066e48a259717d6ad71f47847c6fc957ad3e3da
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