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dataset_info:
features:
- name: file_name
dtype: string
- name: uni
dtype: string
- name: wylie
dtype: string
- name: url
dtype: string
- name: dept
dtype: string
- name: grade
dtype: int64
- name: char_len
dtype: int64
- name: audio_len
dtype: float64
- name: original_id
dtype: string
- name: strata
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 4017714
num_examples: 6988
- name: validation
num_bytes: 212173
num_examples: 368
download_size: 1451597
dataset_size: 4229887
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
---
## Dataset Structure
- **Features:**
- `file_name`: Name of the file.
- `uni`: Tibetan Unicode text.
- `wylie`: Wylie transliteration.
- `url`: Source URL.
- `dept`: Department or category.
- `grade`: Grade/class level.
- `char_len`: Number of characters.
- `audio_len`: Length of audio (seconds).
- `original_id`: Original document or audio ID.
- `strata`: Data strata or group.
- `__index_level_0__`: Index.
- **Splits:** `train`, `validation`
---
## 📊 Split-wise Statistics
| Split | # Samples | Total Char Length | Total Audio Length (hr) |
|--------|----------:|------------------:|-----------------------:|
| train | 6988 | 613604 | 10.5 |
| validation| 368 | 32462 | 0.56 |
| Total | 7356| 646066 |11.06 |
## strata value counts:
| strata | train_count | validation_count |
|-------------------------|------------|------------------|
| 70-80__long__Teaching | 3064 | 161 |
| 70-80__medium__Teaching | 1347 | 71 |
| 80-90__long__Practice | 1011 | 53 |
| 70-80__long__Q&A | 635 | 34 |
| 70-80__long__Prayer | 593 | 31 |
| 70-80__medium__Prayer | 172 | 9 |
| 70-80__short__Teaching | 105 | 6 |
| 70-80__medium__Q&A | 61 | 3 |
## 🚀 Usage
```python
from datasets import load_dataset
ds = load_dataset("your_namespace/your_dataset", split="train") |