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Model: BAAI/AquilaChat2-34B-16K Source: Original Platform
2026-07-27 05:18:06 +08:00
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+---
+license: other
+---
+
+
+![Aquila_logo](./log.jpeg)
+
+
+<h4 align="center">
+    <p>
+        <b>English</b> |
+        <a href="https://huggingface.co/BAAI/AquilaChat2-34B-16K/blob/main/README_zh.md">简体中文</a> 
+    </p>
+</h4>
+
+
+<p align="center">
+  <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>
+</p>
+
+
+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-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, 
+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.
+
+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-16K（Chat model）
+
+### 1. Inference
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+device = torch.device("cuda:0")
+model_info = "BAAI/AquilaChat2-34B-16k"
+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-16K")
+print(out)
+```
+
+
+## License
+
+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)
+
+## Citation
+Feel free to cite the repo if you think Aquila2 is useful.
+
+```python
+@misc{zhang2024aquila2technicalreport,
+      title={Aquila2 Technical Report}, 
+      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},
+      year={2024},
+      eprint={2408.07410},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2408.07410}, 
+}
+```
+
+
+# Acknowledgements
+
+This work is supported by the National Science and Technology Major Project (No. 2022ZD0116300).
+本项目受新一代人工智能国家科技重大专项（No. 2022ZD0116300）支持。