Instructions to use duandaxia/rti-dp-scale with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use duandaxia/rti-dp-scale with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("duandaxia/rti-dp-scale", 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
Add model card for RTI-DP
#1
by nielsr HF Staff - opened
This PR adds a comprehensive model card for the "Real-Time Iteration Scheme for Diffusion Policy" (RTI-DP) model.
It includes:
- Relevant metadata:
pipeline_tag: robotics,library_name: diffusers, andlicense: mit. - Links to the paper, project page, and the official GitHub repository.
- A concise summary of the model's contribution based on the abstract.
- Sample usage instructions, referencing the official codebase for full details and evaluation.
- Citation information and acknowledgements.
- An illustrative GIF from the project's GitHub.
This improves discoverability and provides essential information for users on the Hugging Face Hub.
Thank you!
duandaxia changed pull request status to merged