Update dataset card

README.md

@@ -1,51 +1,117 @@
 ---
-dataset_info:
-  config_name: spanish
-  features:
-  - name: id
-    dtype: string
-  - name: text
-    dtype: string
-  - name: speaker_id
-    dtype: int32
-  - name: chapter_id
-    dtype: int32
-  - name: codes
-    list:
-      list: int16
-  - name: n_frames
-    dtype: int32
-  - name: k_codebooks
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 724046022
-    num_examples: 220701
-  - name: dev
-    num_bytes: 7868779
-    num_examples: 2408
-  - name: test
-    num_bytes: 7885411
-    num_examples: 2385
-  - name: 9_hours
-    num_bytes: 7072272
-    num_examples: 2110
-  - name: 1_hours
-    num_bytes: 777414
-    num_examples: 233
-  download_size: 500804152
-  dataset_size: 747649898
-configs:
-- config_name: spanish
-  data_files:
-  - split: train
-    path: spanish/train-*
-  - split: dev
-    path: spanish/dev-*
-  - split: test
-    path: spanish/test-*
-  - split: 9_hours
-    path: spanish/9_hours-*
-  - split: 1_hours
-    path: spanish/1_hours-*
+license: cc-by-4.0
+language:
+- nl
+- fr
+- de
+- it
+- pl
+- pt
+- es
+task_categories:
+- text-to-speech
+- automatic-speech-recognition
+tags:
+- mimi
+- neural-codec
+- multilingual
+- mls
+- multilingual-librispeech
+- audio-tokens
+pretty_name: Multilingual LibriSpeech Mimi Codes
+size_categories:
+- 1M<n<10M
 ---
+
+# Multilingual LibriSpeech (MLS) — Mimi Codes
+
+Pre-extracted [Kyutai Mimi](https://huggingface.co/kyutai/mimi) neural-codec tokens
+for [Multilingual LibriSpeech](https://huggingface.co/datasets/facebook/multilingual_librispeech) —
+LibriVox audiobooks in 7 non-English languages.
+
+English is intentionally excluded — use
+[shangeth/librispeech-mimi-codes](https://huggingface.co/datasets/shangeth/librispeech-mimi-codes)
+for that.
+
+## Configs (languages)
+
+One HF dataset config per language:
+
+| Config | Language | ISO | Approx hours (train) |
+|---|---|---|---|
+| `dutch`      | Dutch       | nl | ~1.5k |
+| `french`     | French      | fr | ~1.1k |
+| `german`     | German      | de | ~3.3k |
+| `italian`    | Italian     | it | ~250  |
+| `polish`     | Polish      | pl | ~100  |
+| `portuguese` | Portuguese  | pt | ~160  |
+| `spanish`    | Spanish     | es | ~920  |
+
+## Splits (per config)
+
+| Split | Description |
+|---|---|
+| `train`   | full training set |
+| `dev`     | development |
+| `test`    | test |
+| `9_hours` | low-resource ~9h training subset |
+| `1_hours` | low-resource ~1h training subset |
+
+## Schema
+
+| Column | Type | Notes |
+|---|---|---|
+| `id` | string | utterance ID, format `{speaker}_{chapter}_{segment}` |
+| `text` | string | transcript, mixed-case as-is from MLS |
+| `speaker_id` | int32 | speaker ID (parsed from MLS string) |
+| `chapter_id` | int32 | chapter ID |
+| `codes` | `int16[k=8][n_frames]` | Mimi codebook indices @ 12.5 fps |
+| `n_frames` | int32 | |
+| `k_codebooks` | int32 | 8 |
+
+## Extraction details
+
+- **Codec:** [`kyutai/mimi`](https://huggingface.co/kyutai/mimi) @ 24 kHz, 12.5 fps
+- **Resampling:** MLS audio is 48 kHz opus → resampled to 24 kHz at extraction
+- **Codebooks:** all 8 extracted; slice `codes[:k]` for fewer
+- **Source:** [`facebook/multilingual_librispeech`](https://huggingface.co/datasets/facebook/multilingual_librispeech)
+
+## Usage
+
+```python
+from datasets import load_dataset
+import torch
+
+ds = load_dataset("shangeth/mls-mimi-codes", "german", split="dev")
+ex = ds[0]
+codes = torch.tensor(ex["codes"], dtype=torch.long)  # [8, n_frames]
+print(ex["id"], "| speaker:", ex["speaker_id"], "|", ex["text"][:60])
+
+# Decode back to 24 kHz audio
+from transformers import MimiModel
+mimi = MimiModel.from_pretrained("kyutai/mimi").cuda().eval()
+with torch.no_grad():
+    wav = mimi.decode(codes.unsqueeze(0).cuda()).audio_values[0].cpu()
+```
+
+## Citation
+
+```bibtex
+@misc{wren2026,
+  title  = {Wren: A Family of Small Open-Weight Models for Unified Speech-Text Modelling},
+  author = {Shangeth Rajaa},
+  year   = {2026},
+  url    = {https://github.com/shangeth/wren}
+}
+
+@inproceedings{pratap2020mls,
+  title     = {MLS: A Large-Scale Multilingual Dataset for Speech Research},
+  author    = {Pratap, Vineel and Xu, Qiantong and Sriram, Anuroop and Synnaeve, Gabriel and Collobert, Ronan},
+  booktitle = {Interspeech},
+  year      = {2020}
+}
+```
+
+## License
+
+CC-BY-4.0 (inherited from MLS / LibriVox).