Instructions to use thuml/rt1-compressive-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thuml/rt1-compressive-tokenizer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("thuml/rt1-compressive-tokenizer", 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:
- 79e5eb4501d1ac87800db24d5e21936adcaf97f4e88d7a678498963bdbb06d63
- Size of remote file:
- 518 MB
- SHA256:
- 7c8194f83617137ef0a002a15d60c6ee222bcd2442afb4ed704a7918496cc073
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