Update README.md

README.md

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 ---
-license: apache-2.0
+annotations_creators:
+- found
+language_creators:
+- found
+language:
+- ar
+- de
+- en
+- es
+- fr
+- hi
+- id
+- it
+- ja
+- ko
+- nl
+- pl
+- pt
+- ru
+- sv
+- th
+- tr
+- uk
+- vi
+- zh
+license:
+- apache-2.0
+multilinguality:
+- multilingual
+pretty_name: UTS-Datasets
+size_categories:
+- 10M<n<100M
+source_datasets:
+- opus-100
+- opus_ccmatrix
+- opus_paracrawl
+- open_subtitles
+- wmt19
+- wmt20
+- wmt21
+task_categories:
+- translation
+task_ids:
+- translation
 ---
+
+# UTS-Datasets
+
+Processed parallel training and validation data for the [Universal Translation System](https://github.com/code-with-zeeshan/universal-translation-system). Generated by the UTS data pipeline with quality enhancement stages.
+
+## Dataset Contents
+
+### Files
+
+| File | Description |
+|------|-------------|
+| `train_final.txt` | ~4M parallel sentences (all language pairs, sampled & augmented) |
+| `val_final.txt` | ~100K validation sentences (held out from training) |
+| `vocab/` | Script-grouped SentencePiece vocabulary packs (6 groups × 32K tokens) |
+| `pipeline_state.json` | Pipeline checkpoint state for resumability |
+
+### Language Coverage
+
+20 languages, 190 directional pairs:
+
+| Group | Languages |
+|-------|-----------|
+| Latin | en, es, fr, de, it, pt, nl, sv, pl, id, vi, tr |
+| CJK | zh, ja, ko |
+| Arabic | ar |
+| Devanagari | hi |
+| Cyrillic | ru, uk |
+| Thai | th |
+
+### Training Distribution (top pairs)
+
+| Pair | Sentences |
+|------|-----------|
+| en-es | 400K |
+| en-fr | 400K |
+| en-de | 400K |
+| en-zh | 300K |
+| en-ru | 300K |
+| en-ja | 200K |
+| en-ar | 200K |
+| en-pt | 200K |
+| en-it | 200K |
+| en-hi | 100K |
+| Others (10 pairs) | 60K-100K each |
+| Non-English pivots (14 pairs) | 40K each |
+
+## Data Processing Pipeline
+
+The data was processed through the UTS pipeline stages:
+
+1. **Download** — OPUS-100 + supplementary sources (CCMatrix, ParaCrawl, OpenSubtitles, WMT)
+2. **Sampling** — Length filtering (16-128 tokens), language detection, deduplication
+3. **Augmentation** — False friends replacement, idiom insertion, pivot backtranslation
+4. **Knowledge Distillation** — NLLB-3.3B teacher → soft labels (GPU-only stage)
+5. **Quality Filtering** — COMET-22 neural quality scoring (threshold 0.7)
+6. **Vocabulary** — SentencePiece training per script group (unigram model, 32K tokens)
+
+## Usage
+
+```bash
+# Download via HF Hub
+pip install huggingface_hub
+huggingface-cli download code-with-zeeshan/UTS-Datasets --repo-type dataset --local-dir ./uts_data
+
+# Use with UTS training
+uts train --full --config config/override/my_config.yaml --hub-repo-id code-with-zeeshan/UTS-Datasets
+```
+
+## Data Format
+
+Each line in `train_final.txt` / `val_final.txt`:
+```
+<langpair> ||| <source_text> ||| <target_text>
+```
+
+Example:
+```
+en-es ||| Hello world ||| Hola mundo
+```
+
+## Recreating This Dataset
+
+```bash
+uts config --interactive
+# Enable all stages: download, sample, augment, create_ready,
+#   validate, vocab, wiki_bt, knowledge_distillation, comet
+uts data --pipeline --config config/override/my_config.yaml --hub-repo-id code-with-zeeshan/UTS-Datasets
+```
+
+## License
+
+Apache 2.0