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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** 2023.10.25 🔥 **AquilaChat2-34B v1.2** is based on the previous **AquilaChat2-34B**. The AquilaChat2-34B model is close to or exceeds the level of GPT3.5 in the subjective evaluation of 8 secondary ability dimensions. The additional details of the Aquila model will be presented in the official technical report. Please stay tuned for updates on official channels. ## Quick Start AquilaChat2-34B（Chat model） ### 1. Inference ```python from transformers import AutoTokenizer, AutoModelForCausalLM from transformers import BitsAndBytesConfig import torch device = torch.device("cuda:0") model_info = "BAAI/AquilaChat2-34B" tokenizer = AutoTokenizer.from_pretrained(model_info, trust_remote_code=True) 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_info, trust_remote_code=True, torch_dtype=torch.bfloat16, # quantization_config=quantization_config, # Uncomment this line for 4bit quantization ) model.eval() model.to(device) text = "请给出10个要到北京旅游的理由。" from predict import predict out = predict(model, text, tokenizer=tokenizer, max_gen_len=200, top_p=0.9, seed=123, topk=15, temperature=1.0, sft=True, device=device, model_name="AquilaChat2-34B") print(out) ``` ## License Aquila2 series open-source model is licensed under [ BAAI Aquila Model Licence Agreement](https://huggingface.co/BAAI/AquilaChat2-34B/blob/main/BAAI-Aquila-Model-License%20-Agreement.pdf)