Instructions to use shadow-llm/robot-dog-detached-shadow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shadow-llm/robot-dog-detached-shadow with Transformers:
# Load model directly from transformers import AutoModelForCausalLMWithHiddenProjection model = AutoModelForCausalLMWithHiddenProjection.from_pretrained("shadow-llm/robot-dog-detached-shadow", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add model card and robotics tag
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the community science team at Hugging Face. I noticed this repository was missing a detailed model card and metadata.
This PR adds:
- A link to the paper: ShadowPEFT: Shadow Network for Parameter-Efficient Fine-Tuning.
- A link to the official GitHub repository.
- The
roboticspipeline tag, as this framework is designed for efficient adaptation in scenarios like edge computing and robotics (e.g., robot intent generation). - A sample usage section based on the README to help users load the model with the
shadow-peftlibrary.
shadow-seven changed pull request status to merged