Instructions to use cuongdev/tonghop-v3-2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/tonghop-v3-2000 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/tonghop-v3-2000", 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:
- 75a93020be346a39e2efb07c0fa0ed4491e21a5d385d2dcd11ffd77272452e52
- Size of remote file:
- 3.46 GB
- SHA256:
- 9a04300dad8fc8c27674d59ffb9904c8704075e1408e57435dabcbe4555e042e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.