File size: 2,097 Bytes
51d368e 3ee3ce6 51d368e e9b1b11 51d368e e9b1b11 51d368e 3ee3ce6 51d368e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 | # Nepali Education SFT Dataset
A high-quality Nepali-language Supervised Fine-Tuning (SFT) dataset designed for instruction-following and educational question-answering tasks.
The dataset is structured in a conversational format and contains Nepali educational instructions and responses along with detailed source and generation metadata. It was developed with emphasis on data integrity, language purity, structural consistency, intent coverage, and dataset quality assurance.
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## 📌 Dataset Overview
| Property | Value |
|---|---:|
| Dataset Records | 1999 |
| Columns | 19 |
| Language | Nepali |
| Script | Devanagari |
| Task Type | SFT / Instruction Following |
| Data Format | JSONL |
| Conversation Format | Yes |
| Malformed Records | 0 |
| Incomplete Records | 0 |
| Duplicate IDs | 0 |
| Duplicate Complete Rows | 0 |
| Duplicate Questions | 0 |
| Near-Duplicate Question Pairs | 0 |
| Strong Near-Duplicate Pairs | 0 |
| Intent Coverage | 100% |
| Rows Requiring Review | 0 |
| Corrupted Rows | 0 |
| Reported Overall Quality Score | 100% |
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# 🎯 Purpose
The primary purpose of this dataset is to provide high-quality Nepali educational instruction-response examples suitable for Supervised Fine-Tuning of Large Language Models.
The dataset is designed to support models in learning:
- Nepali instruction following
- Educational question answering
- Conversational interaction
- Intent recognition
- Nepali-language response generation
- Educational knowledge delivery
- Different question-answering behaviors
The dataset also contains metadata that can be used for dataset analysis, filtering, auditing, and future quality-control workflows.
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# 🧠 Dataset Design
The dataset follows a structured conversational SFT format.
Each example contains a `conversations` field representing the interaction between the user and the assistant.
Conceptually, an example follows the structure:
```json
{
"id": "1",
"conversations": [
{
"role": "user",
"content": "..."
},
{
"role": "assistant",
"content": "..."
}
]
} |