---
language: vi
license: apache-2.0
tags:
- tokenizer
- unigram
- vietnamese
- xnli
- nlp-research
datasets:
- facebook/xnli
---
# NIRVLab — Unigram Tokenizer for Vietnamese XNLI
A **Unigram Language Model** tokenizer trained from scratch on the Vietnamese (`vi`) subset
of the [facebook/xnli](https://huggingface.co/datasets/facebook/xnli) dataset.
## Training Details
| Parameter | Value |
|---|---|
| Algorithm | Unigram LM (SentencePiece-style) |
| Vocabulary size | 8,000 |
| Special tokens | `, , , , ` |
| Corpus | `facebook/xnli` / `vi` — all splits |
| Corpus size | 800,404 sentences |
| Normalizer | Nmt + NFC Unicode |
| Pre-tokenizer | Metaspace (▁ prefix) |
| Shrinking factor | 0.75 |
| Max piece length | 16 |
## Evaluation Metrics
| Metric | Value |
|---|---|
| Tokens / char | `0.2967` |
| Fertility (tokens / word) | `1.3142` |
| Avg sequence length | `24.81` tokens |
| Vocabulary coverage | `1.0000` |
## Usage
```python
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("NIRVLab/xnli-unigram-vi")
tokens = tokenizer("Xin chào thế giới!", return_tensors="pt")
```