Datasets:
language:
- en
- ar
pretty_name: DeepLatent bilingual tokenizer-data
size_categories:
- 1M<n<10M
task_categories:
- text-generation
tags:
- arabic
- english
- bilingual
- tokenizer-training
DeepLatent bilingual tokenizer-data
Balanced English/Arabic corpus for tokenizer training. The two languages carry essentially the same number of Unicode codepoints, so a BPE/WordPiece tokenizer trained on this corpus sees equal representation of both languages by character content.
Composition
| Slice | Source | Filter | Rows | Chars |
|---|---|---|---|---|
| English | almaghrabima/deeplatent-hq-merged-dedup-token-counts |
GlotLID language == "English" |
3,980,035 | 12,377,830,142 |
| Arabic | AdaMLLab/AraMix-HQ |
mmbert_score >= 0.2784 ∧ language != "English" |
2,380,570 | 12,380,271,596 |
| Total | 6,360,605 | 24,758,101,738 |
The Arabic threshold mmbert_score >= 0.2784 was chosen so the Arabic char
count matches the English char count (balancing the two languages). This
yields the top ~7% highest-scoring Arabic content in AraMix-HQ.
Language labels come from GlotLID (cis-lmu/glotlid) run on the first 2000
characters of each document. The HQ corpus is fully labeled; the AraMix-HQ
source was partially labeled (~38.5% of shards) — remaining Arabic rows in
this merged release default to "Arabic" since labeled AraMix-HQ shards were
96.4% Arabic.
Schema
| Column | Type | Description |
|---|---|---|
text |
string | Document text |
source |
string | Original sub-source (e.g. ar, en, lightonai/ArabicWeb24) |
language |
string | GlotLID label: "English", "Arabic", or raw lang_Script |
origin |
string | "hq" or "aramix" |
File layout
en_00000.parquet…en_00222.parquet— 223 English shardsar_00000.parquet…ar_00178.parquet— 179 Arabic shards
Each file is zstd-compressed parquet.