README.md

---
license: apache-2.0
language:
- zh
- en
tags:
- openba
pipeline_tag: text-generation
---

# Introduction

OpenBA is an open-source bilingual language model equipped with 15 billion parameters, built on the T5 architecture.

## Open Source Plan

We are excited to unveil two distinguished versions of our model, with another on the horizon:

- [OpenBA-LM](https://huggingface.co/OpenBA/OpenBA-LM): The backbone language models was pre-trained on 340B English, Chinese, and code tokens. 
- [OpenBA-Flan](https://huggingface.co/OpenBA/OpenBA-Flan): We perform supervised fine-tuning on the base model with additional 40B tokens using our collected BiFlan Dataset.
- OpenBA-Chat: coming soon

## Model Description
- **Model type:** Language model
- **Language(s) (NLP):** zh, en (We also offer the possibility for multilingual learning, by using a multilingual tokenizer.)
- **License:** Apache 2.0
- **Resources for more information:**
  - [Paper](https://arxiv.org/abs/2309.10706)
  - [GitHub Repo](https://github.com/OpenNLG/OpenBA/)

# Usage

## Install requirements

```bash
pip install transformers torch>=2.0 sentencepiece
```

## Demo usage 

```python
>>> from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
>>> tokenizer = AutoTokenizer.from_pretrained("OpenBA/OpenBA-Flan", trust_remote_code=True)
>>> model = AutoModelForSeq2SeqLM.from_pretrained("OpenBA/OpenBA-Flan", trust_remote_code=True).half().cuda()
>>> model = model.eval()
>>> query = "<S>" + "介绍一下中国的四大名著，并分别概括其主要内容" + "<extra_id_0>"
>>> inputs = tokenizer(query, return_tensors="pt").to("cuda")
>>> outputs = model.generate(**inputs, do_sample=True, max_new_tokens=256)
>>> response = tokenizer.decode(outputs[0], skip_special_tokens=True)
>>> print(response)
中国的四大名著分别是《红楼梦》、《西游记》、《水浒传》和《三国演义》。它们分别包括故事情节、文化内涵和历史背景等方面的不同特点。《红楼梦》是一部中国古典小说,讲述了贾宝玉、林黛玉、薛宝钗等一群人物在贾府的生活和爱情故事。《西游记》是中国著名小说,描述了孙悟空、猪八戒、沙悟净等一众妖魔鬼怪的冒险历程和故事。《水浒传》是一部中国古典小说,描述了宋江等一百零八位好汉的反抗故事。《三国演义》是中国古代著名小说,讲述了三国时期的历史和战争故事。这些小说在文学、历史、哲学和文化等方面都有着不同的影响和地位。
```