Code-170k-shona / README.md
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---
dataset_info:
features:
- name: conversations
list:
- name: from
dtype: string
- name: value
dtype: string
splits:
- name: train
num_bytes: 328319793
num_examples: 176999
download_size: 164159896
dataset_size: 328319793
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
language:
- sn
license: apache-2.0
task_categories:
- text-generation
- question-answering
pretty_name: Code-170k-shona
size_categories:
- 100K<n<1M
tags:
- code
- programming
- sn
- shona
- african-languages
- low-resource
- multilingual
- instruction-tuning
---
## Dataset Description
**Code-170k-shona** is a groundbreaking dataset containing 176,999 programming conversations, originally sourced from [glaiveai/glaive-code-assistant-v2](https://huggingface.co/datasets/glaiveai/glaive-code-assistant) and translated into Shona, making coding education accessible to Shona speakers.
### 🌟 Key Features
- **176,999 high-quality conversations** about programming and coding
- **Pure Shona 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 Shona-language coding assistants
- Building educational tools for Shona developers
- Researching multilingual code generation
- Creating programming tutorials in Shona
- 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 Shona
### Example
```python
{
"conversations": [
{
"from": "human",
"value": "[Question in Shona]"
},
{
"from": "gpt",
"value": "[Answer in Shona]"
}
]
}
```
## Usage
### Loading the Dataset
```python
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("michsethowusu/Code-170k-shona")
# 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
```bibtex
@dataset{code170k_shona,
title={Code-170k-shona: Programming Conversations in Shona},
year={2025},
publisher={Hugging Face},
url={https://huggingface.co/datasets/michsethowusu/Code-170k-shona}
}
```
## License
This dataset is released under the Apache 2.0 License.
---
**Thank you** for using Code-170k-shona to advance programming education in Shona! 🌍✨