Instructions to use InternRobotics/VLN-PE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InternRobotics/VLN-PE with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("InternRobotics/VLN-PE", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card: Add metadata and links
#1
by nielsr HF Staff - opened
This PR enhances the model card for the VLN-PE benchmark and models.
Key improvements include:
- Metadata: Added
pipeline_tag: robotics,library_name: transformers, andlicense: mitfor better discoverability and standardized information. - Links: Added explicit links to the associated research paper, project page, and the main GitHub repository within the model card content. This provides users with direct access to more detailed information.
- Content: The existing benchmark results table remains unchanged, ensuring no disruption to current information. A citation section has also been added based on the GitHub README.
Please review and merge if these improvements are satisfactory.
kew1046 changed pull request status to merged