Improve model card by linking it to paper

README.md

@@ -1,24 +1,24 @@
 ---
-license: apache-2.0
-library_name: transformers
 base_model: openai/whisper-large-v3
-tags:
-  - audio
-  - automatic-speech-recognition
-  - whisper
-  - hf-asr-leaderboard
+library_name: transformers
+license: apache-2.0
 pipeline_tag: automatic-speech-recognition
+tags:
+- audio
+- automatic-speech-recognition
+- whisper
+- hf-asr-leaderboard
 ---
 
 # Model Card for Lite-Whisper large-v3-fast
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-Lite-Whisper is a compressed version of OpenAI Whisper with LiteASR. See our [GitHub repository](https://github.com/efeslab/LiteASR) and [paper](https://arxiv.org/abs/2502.20583) for details.
+Lite-Whisper is a compressed version of OpenAI Whisper with LiteASR. See our [GitHub repository](https://github.com/efeslab/LiteASR) and [paper](https://arxiv.org/abs/2502.20583) for details. The paper is also available on Hugging Face: [Link to Hugging Face Paper Page](https://hf.co/papers/2502.20583)
 
 ## Benchmark Results
 
-Following is the average word error rate (WER) evaluated on the [ESB datasets](https://huggingface.co/datasets/hf-audio/esb-datasets-test-only-sorted):
+Following is the average word error rate (WER) evaluated on the [ESB datasets](https://huggingface.co/datasets/hf-audio/esb-datasets-test-only-sorted):\
 
 | Model | Average WER (↓) | Encoder Size | Decoder Size |
 |-------|----------------|--------------|--------------|