pytorch bert license:bsd-3-clause region:us
---
license: bsd-3-clause
---
# Hong Lou Meng Fine-tuned Model for Word Alignment

This repository contains a fine-tuned version of the **BERT multilingual model** (`bert-base-multilingual-cased`) on the **Hong Lou Meng** dataset for word alignment tasks. This model is fine-tuned using the [awesome-align](https://github.com/neulab/awesome-align) framework and is designed for Chinese-Vietnamese (Zh-Vn) alignment.

## Model Details

- **Base Model:** `bert-base-multilingual-cased`  
- **Fine-tuned Dataset:** Excerpts from the classic "Hong Lou Meng" novel, annotated with Chinese and Vietnamese sentence pairs.  
- **Alignment Task:** Fine-tuned to align word pairs in parallel texts for translation and linguistic analysis.  

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## Example Usage

Below is an example of how to use this model for word alignment using the `transformers` library:

```python
from transformers import AutoTokenizer, AutoModel
import torch

# Load model and tokenizer
model_name = "username/zh-vn-hongloumeng-align"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModel.from_pretrained(model_name)

# Input sentences (Chinese and Vietnamese)
source_sentence = "第一回 甄士隱夢幻識通靈 賈雨村風塵懷閨秀"
target_sentence = "Hồi thứ nhất: Chân Sĩ Ẩn mộng ảo ngộ đá thiêng, Giả Vũ Thôn phong trần nhớ giai nhân."

# Tokenize inputs
inputs = tokenizer(source_sentence, target_sentence, return_tensors="pt", padding=True, truncation=True)

# Pass through model
outputs = model(**inputs)

# Further processing for alignment visualization or analysis would follow
print("Model outputs:", outputs)
