zul-post-training / README.md
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isiZulu post-training data (Walia format)
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metadata
language:
  - zu
  - en
task_categories:
  - text-generation
  - translation
  - text-classification
  - token-classification
  - summarization
pretty_name: isiZulu post-training (Walia-style instruction data)
size_categories:
  - 100K<n<1M
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*

zul-post-training

isiZulu instruction / chat data compiled from public datasets in the style of Walia-LLM (Azime et al., 2024, arXiv:2402.08015), in the same row format as SaarAI/kin-post-training and SaarAI/amh-post-training: task datasets (translation, classification, tagging, NER, generation) are converted to instructions using paraphrased templates (templates.json), and existing instruction / chat sets are added as-is.

961,834 train / 4,859 validation rows. Validation is a random per-task holdout (0.5%, 20-1000 rows per task).

Columns

id, source, task, instruction_lang (zul or en = language of the template, native = source already an instruction/chat set), instruction, input, output, messages (chat form: list of role/content dicts, multi-turn for chat sources; for multi-turn rows instruction / output are the first user / assistant turn).

Tasks

task rows
translation_zul_en 207,229
translation_en_zul 207,229
code_chat 176,492
chat 88,624
instruction_following 83,267
question_answering 56,641
text_continuation 40,000
generation 24,405
summarization 19,885
dialogue 9,996
text_simplification 9,976
paraphrase_identification 9,928
event_linking 9,733
named_entity_recognition 5,844
translation 5,216
hate_speech_detection 2,737
intent_classification 2,240
title_generation 1,791
article_generation 1,791
aya_human 1,652
pos_tagging 753
topic_classification 701
news_topic_classification 563

Sources

source key dataset note
autshumato_zul Mehgoss/sa-languages-translation (zu-en, autshumato) en-zu government / health / agriculture sentence pairs
vukuzenzele_zul dsfsi/vukuzenzele-sentence-aligned (eng-zul) government-newspaper pairs (lower-cased); alignment score >= 0.8
govza_cabinet dsfsi/govza-sa-cabinet-statements-sentence-aligned (eng-zul) cabinet statements; alignment score >= 0.8
smol_sent, smol_doc google/smol (smolsent / smoldoc en_zu) professional en->zu sentence and document translations
sib200 Davlan/sib200 (zul_Latn) topic classification (7 classes)
injongo_intent masakhane/InjongoIntent (zul) intent classification (40 intents)
za_isizulu_news dsfsi/za-isizulu-siswati-news Isolezwe headline topic classification (5 classes)
afrihate afrihate/afrihate (zul) hate / abuse detection (3 classes)
masakhapos masakhane/masakhapos (zul) UPOS tagging
masakhaner2 MasakhaNER 2.0 (zul train, GitHub) named entity recognition (PER / LOC / ORG)
wikipedia_zu wikimedia/wikipedia (20231101.zu) Wikipedia -> article / title generation (>= 50 words)
fineweb2_zul HuggingFaceFW/fineweb-2 (zul_Latn) web text -> text continuation (40k sample)
gsma_conversations_zul israel/zulu (train + validation) grounded multi-agent conversations (GSMA pipeline)
multiturn_combined_zul israel/multiturn_combined (zulu) multi-turn conversations
wikiconversations_zul israel/WikiConversations (isizulu) multi-turn conversations grounded in Wikipedia
african_ultrachat_zul masakhane/african-ultrachat (Zulu train) multi-turn chat
kakugo_zul ptrdvn/kakugo-zul synthetic chat; <think> blocks removed
smoltalk_zul 2b2e/smoltalk-zulu-mtl machine-translated SmolTalk (system turns dropped)
self_instruct_zul 2b2e/zulu-self_instruct-syn synthetic self-instruct
code170k_zul michsethowusu/Code-170k-zulu machine-translated code Q&A chat
alpaca_zul saillab/alpaca-zulu-cleaned machine-translated Alpaca
dolly_zul saillab/taco-datasets (Dolly-15k Zulu) machine-translated Dolly
aya_* CohereLabs/aya_collection_language_split (zulu train) Aya mix (translated); each sub-dataset capped at 10k
inkuba_mafand, inkuba_afriqa lelapa/Inkuba-instruct (isizulu_train) MAFAND news MT and AfriQA, Inkuba's own isiZulu instructions

Row counts per source key:

source rows
autshumato_zul 390,256
code170k_zul 176,492
alpaca_zul 40,317
fineweb2_zul 40,000
smoltalk_zul 39,650
kakugo_zul 36,128
self_instruct_zul 28,878
govza_cabinet 17,396
dolly_zul 14,072
aya_SODA_inst_T 9,996
aya_Wiki_split_inst_T 9,976
aya_Adversarial_QA_T 9,967
aya_CNN_Daily_Mail_T 9,950
aya_Flan_GEM_wiki_lingua_T 9,935
aya_PAWS_Wiki_T 9,928
aya_PIQA_T 9,926
aya_Mintaka_inst_T 9,911
aya_Flan_CoT_submix_T 9,826
aya_HotpotQA_T 9,801
aya_Xlel_wd_inst_T 9,733
aya_Dolly_v2_T 9,689
aya_NQ_Open_T 8,549
aya_Flan_Coqa_T 6,408
masakhaner2 5,844
inkuba_mafand 5,216
african_ultrachat_zul 4,899
vukuzenzele_zul 4,404
aya_Flan_lambada_T 4,156
wikipedia_zu 3,582
multiturn_combined_zul 3,547
gsma_conversations_zul 2,796
afrihate 2,737
injongo_intent 2,240
smol_sent 1,724
aya_Aya_Dataset 1,652
wikiconversations_zul 1,604
aya_WIKI_QA_T 1,037
masakhapos 753
aya_Joke_explaination_inst_T 734
sib200 701
smol_doc 678
za_isizulu_news 563
aya_Flan_unified_QA_T 536
inkuba_afriqa 296
aya_AfriQA_inst 210

Filtering

  • Chat / instruction sources: system turns dropped, <think> blocks removed, conversations with an empty or literal "None" turn dropped, decoding-collapse (a word repeated 8+ times in a row, or very low compressibility) dropped, and GlotLID (cis-lmu/glotlid) must give zul_Latn >= 0.5 on the assistant text (code chat excluded).
  • Translation pairs: zu/en character-length ratio 0.5-3.0, at least 2 words per side, identical pairs dropped.
  • 14,978 exact duplicates were removed (same task + input/instruction + output; full conversation for chat).
reason rows removed
aya_SODA_inst_T: over cap 10000 1,181,582
aya_Wiki_split_inst_T: over cap 10000 979,944
aya_Xlel_wd_inst_T: over cap 10000 513,112
aya_HotpotQA_T: over cap 10000 345,476
aya_NQ_Open_T: over cap 10000 165,850
aya_CNN_Daily_Mail_T: over cap 10000 90,000
aya_Flan_CoT_submix_T: over cap 10000 81,910
aya_PAWS_Wiki_T: over cap 10000 39,401
aya_Flan_GEM_wiki_lingua_T: over cap 10000 17,147
wikipedia_zu: < 50 words 9,770
aya_PIQA_T: over cap 10000 6,113
aya_Dolly_v2_T: over cap 10000 4,808
kakugo_zul: not isiZulu (GlotLID) 4,519
aya_Mintaka_inst_T: over cap 10000 4,000
self_instruct_zul: not isiZulu (GlotLID) 3,959
autshumato_zul: bad pair (length ratio / too short / identical) 3,509
govza_cabinet: alignment score < 0.8 3,493
smoltalk_zul: decoding collapse 2,728
smoltalk_zul: not isiZulu (GlotLID) 2,004
aya_NQ_Open_T: not isiZulu (GlotLID) 1,438
alpaca_zul: not isiZulu (GlotLID) 1,266
dolly_zul: not isiZulu (GlotLID) 918
kakugo_zul: malformed / empty / None turn 735
vukuzenzele_zul: alignment score < 0.8 421
aya_Dolly_v2_T: not isiZulu (GlotLID) 296
code170k_zul: malformed / empty / None turn 263
aya_Xlel_wd_inst_T: not isiZulu (GlotLID) 253
code170k_zul: decoding collapse 233
inkuba_afriqa: empty instruction / target 187
aya_Flan_CoT_submix_T: not isiZulu (GlotLID) 172
govza_cabinet: bad pair (length ratio / too short / identical) 134
aya_HotpotQA_T: not isiZulu (GlotLID) 126
aya_Flan_lambada_T: not isiZulu (GlotLID) 123
multiturn_combined_zul: not isiZulu (GlotLID) 115
aya_PIQA_T: not isiZulu (GlotLID) 67
self_instruct_zul: decoding collapse 64
aya_Flan_GEM_wiki_lingua_T: not isiZulu (GlotLID) 55
wikiconversations_zul: not isiZulu (GlotLID) 51
aya_CNN_Daily_Mail_T: not isiZulu (GlotLID) 34
aya_AfriQA_inst: not isiZulu (GlotLID) 29
aya_Wiki_split_inst_T: not isiZulu (GlotLID) 24
vukuzenzele_zul: bad pair (length ratio / too short / identical) 23
gsma_conversations_zul: not isiZulu (GlotLID) 20
aya_Adversarial_QA_T: not isiZulu (GlotLID) 18
aya_Aya_Dataset: not isiZulu (GlotLID) 11
alpaca_zul: decoding collapse 10
aya_Flan_GEM_wiki_lingua_T: decoding collapse 10
multiturn_combined_zul: decoding collapse 9
aya_Dolly_v2_T: decoding collapse 9
aya_Mintaka_inst_T: not isiZulu (GlotLID) 8
aya_PAWS_Wiki_T: not isiZulu (GlotLID) 8
aya_Xlel_wd_inst_T: decoding collapse 7
aya_Xlel_wd_inst_T: malformed / empty / None turn 7
dolly_zul: decoding collapse 5
aya_Adversarial_QA_T: decoding collapse 5
aya_Flan_unified_QA_T: not isiZulu (GlotLID) 4
aya_PIQA_T: decoding collapse 4
aya_SODA_inst_T: not isiZulu (GlotLID) 4
kakugo_zul: decoding collapse 3
aya_Flan_CoT_submix_T: decoding collapse 2
aya_WIKI_QA_T: not isiZulu (GlotLID) 2
smol_sent: bad pair (length ratio / too short / identical) 1
wikiconversations_zul: malformed / empty / None turn 1
african_ultrachat_zul: malformed / empty / None turn 1
aya_Flan_Coqa_T: decoding collapse 1

Known limitations (please read)

  • The isiZulu instruction templates (templates.json) and translated label names were drafted by an AI model and have not been reviewed by a native speaker.
  • Quality varies by source: code170k_zul, alpaca_zul, dolly_zul, smoltalk_zul and the aya_* (T) sets are machine-translated; kakugo_zul and self_instruct_zul are synthetic. Use the source column to filter or reweight.
  • vukuzenzele_zul and inkuba_mafand text is lower-cased in the source. translation_zul_en outputs are English.
  • Excluded after inspection: Helsinki-NLP/opus-100 en-zu (software UI strings), michsethowusu/english-zulu_sentence-pairs (many misaligned / garbage pairs), the 11.3M wmt22 rows of lelapa/Inkuba-instruct (noisy mined pairs, mostly zu->xx), and FLORES-derived data (benchmark). Benchmarks (AfriXNLI, AfriMMLU, AfriMGSM, Belebele, Uhura) were not used.
  • Only train splits were used (plus israel/zulu validation); test splits of all sources (incl. israel/zulu test, SIB-200, InjongoIntent, AfriHate, MasakhaPOS/NER) remain usable for evaluation.
  • Only exact duplicates were removed; near-duplicates and overlap between sources (e.g. Wikipedia vs. FineWeb-2, Aya vs. Inkuba) may remain. Licenses differ per source (Alpaca / Dolly / Aya derived data carry upstream terms; some sources have no license); check each before commercial use.