Datasets:

Congo-digital-service
/

Dataset-Lingala-Alpaca-LLM

dataset_info:
  features:
    - name: instruction
      dtype: string
    - name: input
      dtype: string
    - name: output
      dtype: string
    - name: source_project
      dtype: string
  splits:
    - name: train
      num_bytes: 1667483
      num_examples: 5700
    - name: test
      num_bytes: 288196
      num_examples: 964
  download_size: 607464
  dataset_size: 1955679
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
license: other
license_name: noodl-1.0
license_link: https://licensingafricandatasets.com/nwulite-obodo-license
language:
  - ln
tags:
  - LLM
  - lingala
  - Llama
pretty_name: Lingala Alpaca LLM Dataset
size_categories:
  - 1K<n<10K

Lingala Alpaca LLM Dataset

This dataset contains human-generated instruction-following data in Lingala, inspired by the Alpaca dataset format, covering five task categories (formal, pedagogical, summary, urban, translation) across five public-interest domains, with a balanced representation of stylistic categories and instruction types.

General Statistics

Total volume: 6,664 lines in total.
Number of unique source texts: 1,772.
Structure: The dataset is divided into 5 instruction types, with a total of 6,100 context occurrences. This differs from the final number of lines because some contexts are intentionally reused across different tasks.

Distribution by Instruction Type

The dataset is organized into five instruction categories:

Formal (tasks_frm.json): 1,425 occurrences, covering administrative and standard responses.
Pedagogical (tasks_pdg.json): 1,425 occurrences, covering explanation and teaching tasks.
Summary (tasks_rsm.json): 1,425 occurrences, covering concise summarization tasks.
Urban (tasks_urb.json): 1,425 occurrences, covering everyday and conversational language.
Translation (tasks_trd.json): 400 occurrences, covering translation of source texts.

Distribution by Domain and Complexity

Domains Covered

The dataset covers the following domains:

Agriculture
Governance / Administration
Health
Informal Sector / Urban
Education Each domain contains 1,220 context occurrences.

Complexity Levels

Basic: 2,586 contexts (42.4%).
Intermediate: 1,952 contexts (32.0%).
Complex: 1,562 contexts (25.6%).

Dataset Structure

Splits

The final published dataset is divided into two splits:

Split	Lines
Train	5,700
Test	964
Total	6,664

Fields

Each example contains the following fields:

instruction
input
output
source_project

Dataset Creation

Source Data: instructions and responses written by the CDS team and institutional collaborators (UNDP, partner universities), based on 1,772 unique source texts after cross-batch deduplication.

Format and Purpose

The dataset is published in an instruction-following format compatible with the Hugging Face datasets library. The data is intended for training and fine-tuning AI language models to generate responses in Lingala adapted to different linguistic registers and task types. The dataset covers:

Formal communication
Pedagogical explanations
Everyday and urban conversation
Text summarization
Translation It also provides coverage across several public-interest domains, including agriculture, governance and administration, health, education, and the informal/urban sector.

Considerations for Using the Data

This dataset intentionally covers 5 broad domains (agriculture, governance, health, informal sector, education) but remains modest in size (6,664 examples) for a low-resource language — users should expect limited lexical and stylistic coverage outside these domains.

Usage

To load this dataset:

from datasets import load_dataset
dataset = load_dataset("Congo-digital-service/Dataset-Lingala-Alpaca-LLM")
print(dataset)

Language

Lingala (ln)

License

This dataset is published under the Nwulite Obodo Open Data License (NOODL-1.0), a license designed for the equitable sharing of African datasets.

This dataset, Dataset-Lingala-Alpaca-LLM (Congo-digital-service/Dataset-Lingala-Alpaca-LLM), was created by Congo Digital Services (CDS SARL) (https://www.congo-digital.com/) in August 2026 in collaboration with the MALOBA community (https://maloba.congo-digital.com/), Radio Rurale, the Service National des Grandes Endémies de Brazzaville, the Faculté des Lettres et des Langues Vivantes, Université Marien Ngouabi (UMNG), the Ministry of Posts, Telecommunications and Digital Economy of the Republic of Congo, and UNDP Congo. It is licensed under the Nwulite Obodo Open Data License (https://licensingafricandatasets.com/nwulite-obodo-license).

In exchange for use of this dataset, users from developing countries are required to provide: Use of the dataset (no additional benefit required). Users from high-income countries or commercial entities are additionally required to publicly acknowledge and credit the Maloba Project (UNDP Republic of Congo — language digitalisation initiative) in any publication, product, model, or output derived from this dataset. To fulfil this requirement, contact contact@congo-digital.com or visit https://www.congo-digital.com/contact.

Creators

Congo Digital Services (CDS SARL) — https://www.congo-digital.com/
In collaboration with:
- the MALOBA community — https://maloba.congo-digital.com/
- SIL Congo
- the Faculté des Lettres et des Langues Vivantes, Université Marien Ngouabi (UMNG)
- the Ministry of Posts, Telecommunications and Digital Economy of the Republic of Congo
- UNDP Congo
Created in August 2026