Aquila-7B

<h4 align="center"> <p> <b>English</b> | <a href="https://huggingface.co/BAAI/Aquila-7B/blob/main/README_zh.md">简体中文</a> | <p> </h4>

Aquila Language Model is the first open source language model that supports both Chinese and English knowledge, commercial license agreements, and compliance with domestic data regulations.

• 🌟 Supports open source commercial licenses. The source code of the Aquila series models is based on the Apache 2.0 agreement, while the model weight is based on the BAAI Aquila Model License Agreement. Users can use it for commercial purposes as long as they meet the licensing restrictions.

• ✍️ Possesses Chinese and English knowledge. The Aquila series model is trained from scratch on a high-quality corpus of Chinese and English languages, with Chinese corpora accounting for about 40%, ensuring that the model accumulates native Chinese world knowledge during the pre-training phase, rather than translated knowledge.

• 👮‍♀️ Complies with domestic data regulations. The Chinese corpora of the Aquila series models come from Intelligence Source's accumulated Chinese datasets over the years, including Chinese internet data from over 10,000 sources (more than 99% of which are domestic sources), as well as high-quality Chinese literature and book data supported by authoritative domestic organizations. We will continue to accumulate high-quality and diverse datasets and incorporate them into the subsequent training of the Aquila base models.

• 🎯 Continuous improvements and open sourcing. We will continue to improve training data, optimize training methods, and enhance model performance, cultivate a flourishing "model tree" on a better base model foundation, and continuously update open-source versions.

The additional details of the Aquila model will be presented in the official technical report. Please stay tuned for updates on official channels, including the FlagAI GitHub repository, FlagAI's Zhihu account and FlagAI's official technical communication group.

We will continue to release improved versions of Aquila model as open source.

• 2023/08/15 ：release v0.10
  • Aquila-7B-01 md5: 4279db72e68df1a0705ecc8d4c7be3db
  • Aquila-7B-02 md5: 621f8ce4c8deebe1635f5a09aa4b80f2
  • AquilaChat-7B-01 md5: 22b22ffaed51388ce23f8e328a9b6a18
  • AquilaChat-7B-02 md5: 6e84423fe2837c79c0ced6817c316bd4

Aquila-7B has shown improvements in the FlagEval large model evaluation ("Objective") compared to last version. It achieved improvements of approximately 9.09% on TruthfulQA datasets. For detailed evaluation results, please refer to the website http://flageval.baai.ac.cn. For detailed version change history, see Change Log.

Quick Start Aquila-7B

1. Inference

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_info = "BAAI/Aquila-7B"
tokenizer = AutoTokenizer.from_pretrained(model_info, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_info, trust_remote_code=True)
model.eval()
model.to("cuda:0")

text = "汽车EDR是什么"

tokens = tokenizer.encode_plus(text)['input_ids'][:-1]

tokens = torch.tensor(tokens)[None,].to("cuda:0")


with torch.no_grad():
    out = model.generate(tokens, do_sample=True, max_length=512, eos_token_id=100007)[0]

    out = tokenizer.decode(out.cpu().numpy().tolist())

    print(out)

License

Aquila-7B and AquilaChat-33B open-source model is licensed under BAAI Aquila Model Licence Agreement

Acknowledgements

This work is supported by the National Science and Technology Major Project (No. 2022ZD0116300). 本项目受新一代人工智能国家科技重大专项（No. 2022ZD0116300）支持。