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README.md
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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-
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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
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### 1. Inference
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from transformers import AutoTokenizer, AutoModelForCausalLM
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from transformers import BitsAndBytesConfig
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model_info = "BAAI/AquilaChat2-7B"
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tokenizer = AutoTokenizer.from_pretrained(model_info, trust_remote_code=True)
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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,
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model_name="AquilaChat2-
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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-
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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/AquilaChat2-70B/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**, **Aquila2-34B** and **Aquila2-70B** , as well as **AquilaChat2**, the chat models, namely **AquilaChat2-7B**, **AquilaChat2-34B** and **AquilaChat2-70B**, 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
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### 1. Inference
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from transformers import AutoTokenizer, AutoModelForCausalLM
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from transformers import BitsAndBytesConfig
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model_info = "BAAI/AquilaChat2-70B"
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tokenizer = AutoTokenizer.from_pretrained(model_info, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(model_info, trust_remote_code=True, torch_dtype=torch.bfloat16)
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model.eval()
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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,
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model_name="AquilaChat2-70B")
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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/AquilaChat2-70B/blob/main/BAAI-Aquila-Model-License-Agreement.pdf)
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