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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/AquilaChat2-7B-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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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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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 AquilaChat2-7B-16K（Chat model） |
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### 1. Inference |
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```python |
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import torch |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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from transformers import BitsAndBytesConfig |
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device = torch.device("cuda:0") |
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model_info = "BAAI/AquilaChat2-7B-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.float16, |
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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=0.95, |
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seed=1234, topk=100, temperature=0.9, sft=True, device=device, |
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model_name="AquilaChat2-7B-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/AquilaChat2-7B-16K/blob/main/BAAI-Aquila-Model-License%20-Agreement.pdf) |
