Instructions to use hjgp/tt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hjgp/tt with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hjgp/tt", 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:
- ba29b306b5c4a918e6287b0293dd9dd206e76fbe607ce65fd3c04b78cc6805ce
- Size of remote file:
- 492 MB
- SHA256:
- 192bdb36a624965be5181f32116a09d952dfc7a9730a133b7ac19274b1037fb9
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