Instructions to use Richard-ZZZZZ/MIND-V with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Richard-ZZZZZ/MIND-V with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Richard-ZZZZZ/MIND-V", 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 comprehensive model card for MIND-V
#1
by nielsr HF Staff - opened
This PR adds a comprehensive model card for the MIND-V model, enhancing its discoverability and usefulness on the Hugging Face Hub.
The updates include:
- Adding the
pipeline_tag: roboticsfor better categorization. - Specifying the
license: apache-2.0. - Linking to the official paper: MIND-V: Hierarchical Video Generation for Long-Horizon Robotic Manipulation with RL-based Physical Alignment.
- Providing a direct link to the GitHub repository for code and further details.
- Including a concise model description.
- Adding visual demonstrations (GIFs and a pipeline diagram).
- Integrating a ready-to-use sample inference code snippet from the GitHub repository.
- Adding the BibTeX citation and acknowledgments.
Please review these additions.