Instructions to use Lapisbird/Llama-adaLR-appendix-model-codi_intermediate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lapisbird/Llama-adaLR-appendix-model-codi_intermediate with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Lapisbird/Llama-adaLR-appendix-model-codi_intermediate") model = AutoModel.from_pretrained("Lapisbird/Llama-adaLR-appendix-model-codi_intermediate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card: Add pipeline tag, paper link, code link, and usage example
#1
by nielsr HF Staff - opened
This PR significantly enhances the model card by:
- Adding the
pipeline_tag: text-generationto the metadata, which improves model discoverability on the Hugging Face Hub. - Including a concise description of the model and its purpose, based on the paper's abstract.
- Linking directly to the research paper: Learning When to Stop: Adaptive Latent Reasoning via Reinforcement Learning.
- Providing a link to the official GitHub repository: https://github.com/apning/adaptive-latent-reasoning.
- Adding a sample usage code snippet directly from the GitHub README, demonstrating how to load the model with the
transformerslibrary.
These changes provide users with more comprehensive information for understanding and utilizing the model.