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FreedomIntelligence/AceGPT-7B-chat
AceGPT-7B-chat is a text generation model from FreedomIntelligence. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
AceGPT is a fully fine-tuned generative text model collection based on LlaMA2, particularly in the Arabic language domain. This is the repository for the 7B-chat pre-trained model.
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From the Hugging Face model README
AceGPT is a fully fine-tuned generative text model collection based on LlaMA2, particularly in the
Arabic language domain. This is the repository for the 7B-chat pre-trained model.
We have released the AceGPT family of large language models, which is a collection of fully fine-tuned generative text models based on LlaMA2, ranging from 7B to 13B parameters. Our models include two main categories: AceGPT and AceGPT-chat. AceGPT-chat is an optimized version specifically designed for dialogue applications. It is worth mentioning that our models have demonstrated superior performance compared to all currently available open-source Arabic dialogue models in multiple benchmark tests. Furthermore, in our human evaluations, our models have shown comparable satisfaction levels to some closed-source models, such as ChatGPT, in the Arabic language.
We are from the School of Data Science, the Chinese University of Hong Kong, Shenzhen (CUHKSZ), the Shenzhen Research Institute of Big Data (SRIBD), and the King Abdullah University of Science and Technology (KAUST).
AceGPT famils come in a range of parameter sizes —— 7B and 13B, each size of model has a base category and a -chat category.
Models input text only.
Models output text only.
Experiments on Arabic Vicuna-80, Arabic AlpacaEval. Numbers are the average performance ratio of ChatGPT over three runs. We do not report the results of raw Llama-2 models since they cannot properly generate Arabic texts.
| Arabic Vicuna-80 | Arabic AlpacaEval | |
|---|---|---|
| Phoenix Chen et al. (2023a) | 71.92% ± 0.2% | 65.62% ± 0.3% |
| Phoenix–multiple-langs Chen et al. (2023b) | 71.67% ± 0.7% | 65.36% ± 0.1% |
| Jais-13B-chat Sengupta et al. (2023) | 75.40% ± 1.6% | 74.95% ± 0.2% |
| AceGPT-7B-chat | 94.82% ± 0.2% | 93.81% ± 0.1% |
| AceGPT-13B-chat | 100.88% ± 0.4% | 97.95% ± 0.1% |
ما هي أسماء بعض الممثلين المشهورين الذين بدأوا مسيراتهم المهنية على برودواي؟
كيف يمكنني تحسين مهارات إدارة الوقت الخاصة بي؟
@article{huang2023acegpt,
title={AceGPT, Localizing Large Language Models in Arabic},
author={Huang, Huang and Yu, Fei and Zhu, Jianqing and Sun, Xuening and Cheng, Hao and Song, Dingjie and Chen, Zhihong and Alharthi, Abdulmohsen and An, Bang and Liu, Ziche and others},
journal={arXiv preprint arXiv:2309.12053},
year={2023}
}