

![Aquila_logo](./log.jpeg)


<h4 align="center">
    <p>
        <b>English</b> |
        <a href="https://huggingface.co/BAAI/AquilaChat2-70B-Expr/blob/main/README_zh.md">简体中文</a> 
    </p>
</h4>


We opensource our **Aquila2** series, now including **Aquila2**, the base language models, namely **Aquila2-7B**, **Aquila2-34B** and **Aquila2-70B-Expr** , as well as **AquilaChat2**, the chat models, namely **AquilaChat2-7B**, **AquilaChat2-34B** and **AquilaChat2-70B-Expr**, as well as the long-text chat models, namely **AquilaChat2-7B-16k** and **AquilaChat2-34B-16k**

The additional details of the Aquila model will be presented in the official technical report. Please stay tuned for updates on official channels.

## Quick Start

### 1. Inference

```python
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
from transformers import BitsAndBytesConfig

model_info = "BAAI/Aquila2-70B-Expr"
tokenizer = AutoTokenizer.from_pretrained(model_info, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_info, trust_remote_code=True)
model.eval()
text = "请给出10个要到北京旅游的理由。"
tokens = tokenizer.encode_plus(text)['input_ids']
tokens = torch.tensor(tokens)[None,].to(device)
stop_tokens = ["###", "[UNK]", "</s>"]
with torch.no_grad():
    out = model.generate(tokens, do_sample=True, max_length=512, eos_token_id=100007, bad_words_ids=[[tokenizer.encode(token)[0] for token in stop_tokens]])[0]
    out = tokenizer.decode(out.cpu().numpy().tolist())
    print(out)
```


## License

Aquila2 series open-source model is licensed under [ BAAI Aquila Model Licence Agreement](https://huggingface.co/BAAI/Aquila2-70B-Expr/blob/main/BAAI-Aquila-Model-License-Agreement.pdf)
{"license": "other"}
transformers pytorch aquila text-generation license:other autotrain_compatible endpoints_compatible region:us