Improve model card: Add pipeline tag, paper and code links, and usage example (#1)

- Improve model card: Add pipeline tag, paper and code links, and usage example (35d6d7a3e59101f6f56386c8f44e0c7f35766d42)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -1,10 +1,31 @@
 ---
-library_name: transformers
-license: llama3.2
 base_model: meta-llama/Llama-3.2-1B-Instruct
 datasets:
 - whynlp/gsm8k-aug
+library_name: transformers
+license: llama3.2
 tags: []
+pipeline_tag: text-generation
 ---
 
-Built with Llama
+# Learning When to Stop: Adaptive Latent Reasoning via Reinforcement Learning
+
+This repository contains the model presented in the paper [Learning When to Stop: Adaptive Latent Reasoning via Reinforcement Learning](https://huggingface.co/papers/2511.21581).
+
+Latent reasoning represents a new approach in Transformer language models, aiming to compress reasoning lengths. This model uses a post-SFT reinforcement-learning methodology to optimize latent reasoning length, minimizing it while maintaining accuracy.
+
+Code: [https://github.com/apning/adaptive-latent-reasoning](https://github.com/apning/adaptive-latent-reasoning)
+
+## Sample Usage
+
+You can load these models using the `automodelforcausallm_from_pretrained_latent` function from `src.model_creation`.
+
+```python
+from transformers import AutoTokenizer
+from src.model_creation import automodelforcausallm_from_pretrained_latent
+
+repo_id = "Lapisbird/Llama-adaLR-model-latent-6"
+
+model = automodelforcausallm_from_pretrained_latent(repo_id)
+tokenizer = AutoTokenizer.from_pretrained(repo_id)
+```