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---
license: apache-2.0
language:
- zh
base_model:
- hfl/chinese-lert-base
tags:
- punctuation-restoration
---
<div align="center">
<h1>FireRedChat-punc</h1>
</div>
<div align="center">
<a href="https://fireredteam.github.io/demos/firered_chat/">Demo</a> •
<a href="https://arxiv.org/pdf/2509.06502">FireRedChat Paper</a> •
<a href="https://huggingface.co/FireRedTeam">Huggingface</a>
</div>
## Descriptions
FireRedChat-punc is a fine-tuned `hfl/chinese-lert-base` model designed for punctuation restoration, primarily for post-processing in [FireRedASR](https://github.com/FireRedTeam/FireRedASR).
The model restores the following punctuation marks: [， 。 ？ ！]. It supports both Chinese and English text, enhancing the readability of transcribed text.
## Roadmap
- [x] 2025/09
- [x] Release the fine-tuned punctuation restoration model.
## Usage
RedPost source code [github](https://github.com/FireRedTeam/FireRedChat/tree/main/fireredasr-server/server/redpost)
Below is an example of how to use the FireRedChat-punc model for punctuation restoration:
```bash
git clone https://huggingface.co/hfl/chinese-lert-base FireRedChat-punc/chinese-lert-base
```
```python
import os
from redpost import RedPost, RedPostConfig
punc_model_dir = "./FireRedChat-punc"
post_config = RedPostConfig(
use_gpu=True,
sentence_max_length=30
)
post_model = RedPost.from_pretrained(punc_model_dir, post_config)
batch_post_results = post_model.process([text], ["text"])
text = "".join([r["punc_text"] for r in batch_post_results])
text = re.sub("<unk>|<UNK>|\[unk\]|\[UNK\]", "", text)
print(text)
```
## Use with FireRedASR
This punctuation restoration model can be used together with FireRedASR, refer to [fireredasr-server](https://github.com/FireRedTeam/FireRedChat/blob/main/fireredasr-server/README.md) for setup instructions.
https://github.com/FireRedTeam/FireRedChat/tree/main/fireredasr-server
## License
The model and source code are licensed under the Apache-2.0 license.
### Acknowledgment
- Base model: `hfl/chinese-lert-base` (license: apache-2.0)
- Designed for integration with [FireRedASR](https://github.com/FireRedTeam/FireRedASR). |