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Aquila2-7B/README_zh.md
ModelHub XC 2110d598fa 初始化项目,由ModelHub XC社区提供模型
Model: BAAI/Aquila2-7B
Source: Original Platform
2026-05-18 11:20:10 +08:00

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---
license: other
---
![Aquila_logo](./log.jpeg)
<h4 align="center">
<p>
<a href="https://huggingface.co/BAAI/Aquila2-7B/blob/main/README.md">English</a> |
<b>简体中文</b> |
<p>
</h4>
# 悟道·天鹰Aquila2
我们开源了我们的 **Aquila2** 系列,现在包括基础语言模型 **Aquila2-7B****Aquila2-34B** ,对话模型 **AquilaChat2-7B****AquilaChat2-34B**,长文本对话模型**AquilaChat2-7B-16k** 和 **AquilaChat2-34B-16k**
悟道 · 天鹰 Aquila 模型的更多细节将在官方技术报告中呈现。请关注官方渠道更新。
## 更新/Updates 2024.6.6
我们更新了基础语言模型 **Aquila2-7B**,该模型是基于原版模型经过继续训练得到的,和之前的模型相比,新的模型具备以下优势:
* 更换了具备更大压缩率的tokenizer不同tokenizer的压缩率对比如下面表格
| Tokenizer | Size | Zh | En | Code | Math | Average |
|-----------|-------|--------------------------|--------|-------|-------|---------|
| Aquila2-original | 100k | **4.70** | 4.42 | 3.20 | 3.77 | 4.02 |
| Qwen1.5 | 151k | 4.27 | 4.51 | 3.62 | 3.35 | 3.94 |
| Llama3 | 128k | 3.45 | **4.61** | 3.77 | **3.88** | 3.93 |
| Aquila2-new | 143k | 4.60 | **4.61** | **3.78** | **3.88** | **4.22** |
* 模型支持的最大处理长度从2048增加至8192
## 快速开始使用 Aquila-7B
## 使用方式/How to use
### 1. 推理/Inference
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers import BitsAndBytesConfig
device= "cuda:0"
# 模型名称/Model Name
model_name = 'BAAI/Aquila2-7B'
# 加载模型以及tokenizer
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_name, torch_dtype=torch.bfloat16, trust_remote_code=True,
# quantization_config=quantization_config # Uncomment this one for 4-bit quantization
)
tokenizer = AutoTokenizer.from_pretrained(path, trust_remote_code=True)
model.eval()
model.to(device)
# 对话测试样例/Example
text = "生命的意义是"
tokens = tokenizer.encode_plus(text)['input_ids']
tokens = torch.tensor(tokens)[None,].to(device)
with torch.no_grad():
out = model.generate(tokens, do_sample=False, max_length=128, eos_token_id=tokenizer.eos_token_id)[0]
out = tokenizer.decode(out.cpu().numpy().tolist())
print(out)
```
## 证书/License
`Aquila2系列开源模型使用 [智源Aquila系列模型许可协议](https://huggingface.co/BAAI/Aquila2-7B/blob/main/BAAI-Aquila-Model-License%20-Agreement.pdf)