Add library_name, pipeline_tag and link to code

Hi! I'm Niels from the community science team at Hugging Face. I've opened this PR to enhance the model card for L2T 1B Shared.

The changes include:
- Adding the `text-generation` pipeline tag for better discoverability.
- Specifying the `transformers` library name to enable automated code snippets.
- Including direct links to the paper and the GitHub repository.
- Providing a brief description of the model based on the associated paper.

Please let me know if you have any questions!

README.md

@@ -1,14 +1,21 @@
 ---
-license: mit
 datasets:
 - HuggingFaceTB/smollm-corpus
 language:
 - en
+license: mit
+library_name: transformers
+pipeline_tag: text-generation
 ---
 
 # L2T 1B Shared
 
+This model is a 1B parameter language model pre-trained using the **L2T** framework, as presented in [Enhancing Linguistic Competence of Language Models through Pre-training with Language Learning Tasks](https://huggingface.co/papers/2601.03448).
 
+L2T (Language Learning Tasks) is a pre-training framework that integrates specific language learning tasks alongside standard next-token prediction. Inspired by human language acquisition, L2T transforms raw text into structured input-output pairs to provide explicit linguistic stimulation, improving linguistic competence while maintaining competitive performance on general reasoning tasks.
+
+- **Paper:** [Enhancing Linguistic Competence of Language Models through Pre-training with Language Learning Tasks](https://huggingface.co/papers/2601.03448)
+- **Code:** [https://github.com/gucci-j/l2t](https://github.com/gucci-j/l2t)
 
 ## How to Get Started with the Model
 Use the code below to get started with the model.
@@ -25,7 +32,7 @@ tokenizer = AutoTokenizer.from_pretrained(
 
 
 ## Citation
-```
+```bibtex
 @article{yamaguchi2026enhancinglinguisticcompetencelanguage,
       title={Enhancing Linguistic Competence of Language Models through Pre-training with Language Learning Tasks}, 
       author={Atsuki Yamaguchi and Maggie Mi and Nikolaos Aletras},
@@ -37,6 +44,4 @@ tokenizer = AutoTokenizer.from_pretrained(
       journal={arXiv},
       volume={abs/2601.03448}
 }
-```
-
-
+```