Datasets:

michsethowusu
/

Code-170k-susu

dataset_info:
  features:
    - name: conversations
      list:
        - name: from
          dtype: string
        - name: value
          dtype: string
  splits:
    - name: train
      num_bytes: 328907441
      num_examples: 176999
  download_size: 164453720
  dataset_size: 328907441
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
language:
  - sus
license: apache-2.0
task_categories:
  - text-generation
  - question-answering
pretty_name: Code-170k-susu
size_categories:
  - 100K<n<1M
tags:
  - code
  - programming
  - sus
  - susu
  - african-languages
  - low-resource
  - multilingual
  - instruction-tuning

Dataset Description

Code-170k-susu is a groundbreaking dataset containing 176,999 programming conversations, originally sourced from glaiveai/glaive-code-assistant-v2 and translated into Susu, making coding education accessible to Susu speakers.

🌟 Key Features

176,999 high-quality conversations about programming and coding
Pure Susu language - democratizing coding education
Multi-turn dialogues covering various programming concepts
Diverse topics: algorithms, data structures, debugging, best practices, and more
Ready for instruction tuning of Large Language Models

🎯 Use Cases

Training Susu-language coding assistants
Building educational tools for Susu developers
Researching multilingual code generation
Creating programming tutorials in Susu
Supporting low-resource language AI development

Dataset Structure

Data Fields

conversations: A list of conversation turns, where each turn contains:
- from: The speaker ("human" or "gpt")
- value: The message content in Susu

Example

{
  "conversations": [
    {
      "from": "human",
      "value": "[Question in Susu]"
    },
    {
      "from": "gpt",
      "value": "[Answer in Susu]"
    }
  ]
}

Usage

Loading the Dataset

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("michsethowusu/Code-170k-susu")

# Access training data
train_data = dataset['train']

# Example: Print first conversation
for turn in train_data[0]['conversations']:
    print(f"{turn['from']}: {turn['value']}")

Citation

@dataset{code170k_susu,
  title={Code-170k-susu: Programming Conversations in Susu},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/michsethowusu/Code-170k-susu}
}

License

This dataset is released under the Apache 2.0 License.

Thank you for using Code-170k-susu to advance programming education in Susu! 🌍✨