Instructions to use Season998/Traffic-R1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Season998/Traffic-R1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Season998/Traffic-R1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card: Update pipeline tag, add library name, and abstract
#1
by nielsr HF Staff - opened
This PR enhances the model card by:
- Updating the
pipeline_tagfromreinforcement-learningtorobotics, which more accurately reflects the model's application in real-world traffic signal control systems. This will improve discoverability on the Hugging Face Hub (e.g., viahttps://huggingface.co/models?pipeline_tag=robotics). - Adding
library_name: transformersto the metadata, as the model is based on Qwen and compatible with the Hugging Facetransformerslibrary, enabling easier programmatic access and usage examples on the model page. - Adding the paper abstract to the model card content for better context and information completeness.
Season998 changed pull request status to merged