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---
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license: other
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---
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![Aquila_logo](./log.jpeg)
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<h4 align="center">
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<p>
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<a href="https://huggingface.co/BAAI/AquilaChat2-34B/blob/main/README.md">English</a>
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<b>简体中文</b> |
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</p>
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</h4>
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# 悟道·天鹰(Aquila2)
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我们开源了我们的 **Aquila2** 系列,现在包括基础语言模型 **Aquila2-7B** 和 **Aquila2-34B** ,对话模型 **AquilaChat2-7B** 和 **AquilaChat2-34B**,长文本对话模型**AquilaChat2-7B-16k** 和 **AquilaChat2-34B-16k**
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悟道 · 天鹰 Aquila 模型的更多细节将在官方技术报告中呈现。请关注官方渠道更新。
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## 对话模型性能
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<br>
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<p align="center">
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<img src="chat_metrics.jpeg" width="1024"/>
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<p>
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<br>
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## 快速开始使用 AquilaChat2-34B
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## 使用方式/How to use
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### 1. 推理/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")
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model_info = "BAAI/AquilaChat2-34B"
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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)
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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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tokens = tokenizer.encode_plus(text)['input_ids']
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tokens = torch.tensor(tokens)[None,].to(device)
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stop_tokens = ["###", "[UNK]", "</s>"]
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with torch.no_grad():
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out = model.generate(tokens, do_sample=True, max_length=512, eos_token_id=100007, bad_words_ids=[[tokenizer.encode(token)[0] for token in stop_tokens]])[0]
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out = tokenizer.decode(out.cpu().numpy().tolist())
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print(out)
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```
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## 证书/License
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Aquila2系列开源模型使用 [智源Aquila系列模型许可协议](https://huggingface.co/BAAI/AquilaChat2-7B/blob/main/BAAI-Aquila-Model-License%20-Agreement.pdf)
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