Instructions to use cuongdev/test-vtt-tanh2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/test-vtt-tanh2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cuongdev/test-vtt-tanh2", 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:
- fbac244242e6d62c68c05e11614881fa7f7d9fb2ad015b9ed00987c949134ed0
- Size of remote file:
- 681 MB
- SHA256:
- 5f4e7c3614d4aaf1edeb95a503bb7911d80d663816e3eca353e3e02df3bc0b93
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.