README.md

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license: other
---

![Aquila_logo](./log.jpeg)

<h4 align="center">
    <p>
        <b>English</b> |
        <a href="https://huggingface.co/BAAI/Aquila2-7B/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** and **Aquila2-34B**, as well as **AquilaChat2**, the chat models, namely **AquilaChat2-7B** and **AquilaChat2-34B**, 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.


## Base Model Performance

<br>
<p align="center">
    <img src="base_metrics.jpeg" width="1024"/>
<p>
<br>

## Quick Start  Aquila2-7B

### 1. Inference
Aquila2-7B is a base model that can be used for continuation.

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

device = torch.device("cuda")
model_info = "BAAI/Aquila2-7B"
tokenizer = AutoTokenizer.from_pretrained(model_info, trust_remote_code=True)
quantization_config=BitsAndBytesConfig(
                        load_in_4bit=True,
                        bnb_4bit_use_double_quant=True,
                        bnb_4bit_quant_type="nf4",
                        bnb_4bit_compute_dtype=torch.bfloat16,
                    )
model = AutoModelForCausalLM.from_pretrained(model_info, trust_remote_code=True, torch_dtype=torch.float16,
                                                # quantization_config=quantization_config, # Uncomment this line for 4bit quantization
                                                )
model.eval()
model.to(device)
text = "杭州亚运会的亮点和期待 2023年9月23日至10月8日，杭州将举办第19届亚洲运动会"
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/Aquila2-7B/blob/main/BAAI-Aquila-Model-License%20-Agreement.pdf)