Add task category, LeVo paper, project page, code, and sample usage, and remove redundant license

This PR significantly enhances the dataset card for `SSLD-200` by:

- Adding `task_categories: automatic-speech-recognition` to the metadata, reflecting the dataset's primary use in lyrics transcription and song structure parsing.
- Linking the dataset to its broader context within the `LeVo: High-Quality Song Generation with Multi-Preference Alignment` paper ([https://huggingface.co/papers/2506.07520](https://huggingface.co/papers/2506.07520)), where it serves as an evaluation benchmark.
- Including direct links to the LeVo project page ([https://levo-demo.github.io](https://levo-demo.github.io)) and the `SongGeneration` GitHub repository ([https://github.com/tencent-ailab/songgeneration](https://github.com/tencent-ailab/songgeneration)).
- Adding a "Sample Usage" section with practical code snippets and input guidance derived from the GitHub README, enabling users to easily get started.
- Removing the redundant "License" section from the markdown content, as the license is already correctly specified in the YAML metadata.

These improvements make the dataset card more comprehensive, discoverable, and user-friendly.

README.md

@@ -1,23 +1,72 @@
 ---
-license: apache-2.0
 language:
 - en
 - zh
+license: apache-2.0
 tags:
 - music
+task_categories:
+- automatic-speech-recognition
 ---
 
 # Song Structure and Lyric Dataset (SSLD-200)
 
-DataSet used to evaluate song structure parsing and lyrics transcription. SSLD-200 consists of 200 songs, 100 English and 100 Chinese, collected entirely from YouTube, with a total duration of 13.9 hours. 
+This dataset is used as an evaluation benchmark in the paper [LeVo: High-Quality Song Generation with Multi-Preference Alignment](https://huggingface.co/papers/2506.07520).
+
+Project page: [https://levo-demo.github.io](https://levo-demo.github.io)
+Code: [https://github.com/tencent-ailab/songgeneration](https://github.com/tencent-ailab/songgeneration)
 
-The **lyric_norm** in the format \[structure\]\[start:end\]lyric
+DataSet used to evaluate song structure parsing and lyrics transcription. SSLD-200 consists of 200 songs, 100 English and 100 Chinese, collected entirely from YouTube, with a total duration of 13.9 hours.
+
+The **lyric_norm** in the format \\[structure\\]\\[start:end\\]lyric
  - The structure is the label from StructureAnalysis for the segment.
  - The start and end are the segment’s start and end times.
  - The lyric is the recognized lyrics.
 
+## Sample Usage
+
+To use this dataset in conjunction with the associated `SongGeneration` models, follow these steps for inference.
+
+First, download the required runtime components and a specific model checkpoint:
+
+```bash
+# Download runtime components
+huggingface-cli download lglg666/SongGeneration-Runtime --local-dir ./runtime
+mv runtime/ckpt ckpt
+mv runtime/third_party third_party
+
+# Download a specific model checkpoint (e.g., SongGeneration-base-new)
+huggingface-cli download lglg666/SongGeneration-base-new --local-dir ./songgeneration_base_new
+```
+
+Once setup, you can run the inference script. You need to provide a `ckpt_path` (the directory where you downloaded the model checkpoint), an input `lyrics.jsonl` file, and an `output_path`.
+
+```bash
+sh generate.sh ckpt_path lyrics.jsonl output_path
+```
+
+**Input Format (`lyrics.jsonl`):**
+
+Each line in the `.jsonl` file represents an individual song generation request and must contain the following fields:
+
+-   `idx`: A unique identifier for the output song.
+-   `gt_lyric`: The lyrics and song structure, following the format `[Structure] Text`. For example:
+    `[intro-short] ; [verse] These faded memories of us. I can't erase the tears you cried before. Unchained this heart to find its way. My peace won't beg you to stay ; [bridge] If ever your truth still remains. Turn around and see. Life rearranged its games. All these lessons in mistakes. Even years may never erase ; [inst-short] ; [chorus] Like a fool begs for supper. I find myself waiting for her. Only to find the broken pieces of my heart. That was needed for my soul to love again ; [outro-short]`
+-   `descriptions`: (Optional) Custom text prompt for generation attributes like gender, timbre, genre, emotion, instrument, and BPM (e.g., `"female, dark, pop, sad, piano and drums."`).
+-   `prompt_audio_path`: (Optional) Path to a 10-second reference audio file.
+-   `auto_prompt_audio_type`: (Optional) Used if `prompt_audio_path` is not provided, automatically selects a reference audio based on a given style (e.g., `'Pop'`, `'R&B'`, `'Dance'`, `'Jazz'`, etc.).
+
+Example command:
+
+```bash
+sh generate.sh songgeneration_base_new sample/lyrics.jsonl sample/output
+```
+
+Additional flags can be used for specific inference scenarios, such as `--low_mem` for low-memory inference, `--not_use_flash_attn` to disable Flash Attention, or `--separate` to generate separated vocal and accompaniment tracks.
 
 ## Citation
+
+The dataset itself is detailed in the following work:
 ```
 @misc{tan2025songpreppreprocessingframeworkendtoend,
       title={SongPrep: A Preprocessing Framework and End-to-end Model for Full-song Structure Parsing and Lyrics Transcription}, 
@@ -28,7 +77,4 @@ The **lyric_norm** in the format \[structure\]\[start:end\]lyric
       primaryClass={eess.AS},
       url={https://arxiv.org/abs/2509.17404}, 
 }
-```
-
-## License
-The code and weights in this repository is released in the [LICENSE](LICENSE)  file.
+```