Instructions to use LanguageBind/t2i_ablation_arch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LanguageBind/t2i_ablation_arch with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LanguageBind/t2i_ablation_arch", 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:
- 5f3f9cd04c19e6549845195ae4ce88eddb76f4cde5a3f5b6a2211e33e627d449
- Size of remote file:
- 692 MB
- SHA256:
- 87a5de9b9c79afc22ac5aedbfb41658c7b8ead7cd856dd33dbf46ca475d964d0
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