Add pipeline_tag and library_name to model card

Hi! I'm Niels from the Hugging Face community team.

This PR improves the model card by:
- Moving the metadata to the standard YAML frontmatter format at the top of the file.
- Adding `pipeline_tag: text-classification`, which is the standard tag for reward models.
- Adding `library_name: transformers` as the model utilizes the Transformers library for text encoding and base model loading.

These changes help users discover your model more easily and enable the "Use in Transformers" button on the Hub. The rest of your documentation remains unchanged as it is already very comprehensive!

README.md

@@ -1,12 +1,23 @@
 ---
-license: mit
+base_model:
+- Skywork/Skywork-Reward-Llama-3.1-8B-v0.2
 datasets:
 - openai/summarize_from_feedback
+license: mit
+pipeline_tag: text-classification
+library_name: transformers
+---
+
+---
 base_model:
 - Skywork/Skywork-Reward-Llama-3.1-8B-v0.2
+datasets:
+- openai/summarize_from_feedback
+license: mit
+pipeline_tag: text-classification
+library_name: transformers
 ---
 
-
 # Meta Reward Modeling (MRM)
 
 ## Overview
@@ -172,4 +183,4 @@ If you use this model or code in your research, please cite:
 
 ## License
 
-This model is released under the **MIT License**.
+This model is released under the **MIT License**.