README.md

---
license: mit
task_categories:
- question-answering
language:
- en
tags:
- sunbird
- sunbirdai
pretty_name: Sunbird Salt Documentation
size_categories:
- n<1K
configs:
- config_name: default
  data_files:
  - split: train
    path: chunks/*.json
---

# COCIS WEB INFO

## Dataset Summary
This dataset contains text chucks scraped from its official website and corresponding websites. 
The dataset consists of **JSON chunks**, designed for high-performance streaming and parallel processing. Each chunk represents a discrete unit of data structured for machine learning tasks. 

By sharding the data into chuck files, this repository supports the `datasets` library's streaming mode, allowing users to train models without downloading the entire dataset into RAM—a critical feature for resource-constrained environments or high-concurrency CI/CD pipelines.

## Repository Structure
The data is organized into a `chunks/` directory to maintain a clean root level:

```text
.
├── README.md          # This file
└── chunks/            # Directory containing JSON files
    ├── chunk_1.json
    ├── chunk_2.json
    └── ...
```

## Usage

You can load this dataset directly using the Hugging Face datasets library:

```python
from datasets import load_dataset

# Standard loading
dataset = load_dataset("jimjunior/sunbird_salt_docs")

# Streaming mode (Recommended for many shards)
streamed_dataset = load_dataset("jimjunior/sunbird_salt_docs", streaming=True)
print(next(iter(streamed_dataset["train"])))
```

## Maintenance and Contributions

This dataset was created as part of the Sunbird AI Internship 2026. Its actively mantained by [Beingana Jim Junior](https://www.linkedin.com/in/jim-junior-beingana/).