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license: other |
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<h4 align="center"> |
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<p> |
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<b>English</b> | |
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<a href="https://huggingface.co/BAAI/AquilaChat2-34B-16K/blob/main/README_zh.md">简体中文</a> |
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</p> |
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</h4> |
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<p align="center"> |
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<a href="https://github.com/FlagAI-Open/Aquila2" target="_blank">Github</a> • <a href="https://github.com/FlagAI-Open/Aquila2/blob/main/assets/wechat-qrcode.jpg" target="_blank">WeChat</a> <br> |
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</p> |
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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** |
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2023.10.25 🔥 **AquilaChat2-34B-16K v1.2** is based on the previous **AquilaChat2-34B-16K**. The AquilaChat2-34B-16K-V1.2 has significantly improved long-text synthesis capabilities compared to the V1 version, |
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approaching the level of GPT-3.5-16K. Additionally, the V1.2 version incorporates more conventional instruction fine-tuning corpora, enhancing its performance in non-long-text scenarios compared to the V1 version. |
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The additional details of the Aquila model will be presented in the official technical report. Please stay tuned for updates on official channels. |
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## Quick Start AquilaChat2-34B-16K（Chat model） |
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### 1. Inference |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import torch |
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device = torch.device("cuda:0") |
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model_info = "BAAI/AquilaChat2-34B-16k" |
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tokenizer = AutoTokenizer.from_pretrained(model_info, trust_remote_code=True) |
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quantization_config=BitsAndBytesConfig( |
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load_in_4bit=True, |
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bnb_4bit_use_double_quant=True, |
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bnb_4bit_quant_type="nf4", |
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bnb_4bit_compute_dtype=torch.bfloat16, |
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) |
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model = AutoModelForCausalLM.from_pretrained(model_info, trust_remote_code=True, torch_dtype=torch.bfloat16, |
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# quantization_config=quantization_config, # Uncomment this line for 4bit quantization |
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) |
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model.eval() |
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model.to(device) |
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text = "请给出10个要到北京旅游的理由。" |
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from predict import predict |
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out = predict(model, text, tokenizer=tokenizer, max_gen_len=200, top_p=0.9, |
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seed=123, topk=15, temperature=1.0, sft=True, device=device, |
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model_name="AquilaChat2-34B-16K") |
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print(out) |
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``` |
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## License |
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Aquila2 series open-source model is licensed under [ BAAI Aquila Model Licence Agreement](https://huggingface.co/BAAI/AquilaChat2-34B-16K/blob/main/BAAI-Aquila-Model-License%20-Agreement.pdf) |
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## Citation |
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Feel free to cite the repo if you think Aquila2 is useful. |
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```python |
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@misc{zhang2024aquila2technicalreport, |
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title={Aquila2 Technical Report}, |
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author={Bo-Wen Zhang and Liangdong Wang and Jijie Li and Shuhao Gu and Xinya Wu and Zhengduo Zhang and Boyan Gao and Yulong Ao and Guang Liu}, |
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year={2024}, |
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eprint={2408.07410}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2408.07410}, |
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} |
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``` |
