https://huggingface.co/spaces/Qwen/Qwen2-72B-Instruct\n","updatedAt":"2024-07-16T03:30:01.012Z","author":{"_id":"61e4c4ca1ab24785ac11ba69","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/61e4c4ca1ab24785ac11ba69/1Q1zhhyGSJ9RJG9MzwxVv.jpeg","fullname":"Binyuan Hui","name":"huybery","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":74,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.775611937046051},"editors":["huybery"],"editorAvatarUrls":["https://cdn-avatars.huggingface.co/v1/production/uploads/61e4c4ca1ab24785ac11ba69/1Q1zhhyGSJ9RJG9MzwxVv.jpeg"],"reactions":[{"reaction":"❤️","users":["clem","tnlin","marinaretik","RuPeng"],"count":4}],"isReport":false}},{"id":"66971f10e8ec15fafe09be7d","author":{"_id":"63d3e0e8ff1384ce6c5dd17d","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1674830754237-63d3e0e8ff1384ce6c5dd17d.jpeg","fullname":"Librarian Bot (Bot)","name":"librarian-bot","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":318,"isUserFollowing":false},"createdAt":"2024-07-17T01:32:00.000Z","type":"comment","data":{"edited":false,"hidden":false,"latest":{"raw":"This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [YuLan: An Open-source Large Language Model](https://huggingface.co/papers/2406.19853) (2024)\n* [GEB-1.3B: Open Lightweight Large Language Model](https://huggingface.co/papers/2406.09900) (2024)\n* [A Teacher Is Worth A Million Instructions](https://huggingface.co/papers/2406.19112) (2024)\n* [Aya 23: Open Weight Releases to Further Multilingual Progress](https://huggingface.co/papers/2405.15032) (2024)\n* [A Survey on Large Language Models for Code Generation](https://huggingface.co/papers/2406.00515) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`","html":"
This is an automated message from the Librarian Bot. I found the following papers similar to this paper.
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- YuLan: An Open-source Large Language Model (2024) \n
- GEB-1.3B: Open Lightweight Large Language Model (2024) \n
- A Teacher Is Worth A Million Instructions (2024) \n
- Aya 23: Open Weight Releases to Further Multilingual Progress (2024) \n
- A Survey on Large Language Models for Code Generation (2024) \n
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Abstract
The Qwen2 series, comprising 0.5 to 72 billion parameter models, surpasses prior open models across language understanding, generation, multilingualism, coding, math, and reasoning, with exceptional performance in benchmarks like MMLU, GPQA, HumanEval, GSM8K, BBH, MT-Bench, Arena-Hard, and LiveCodeBench.
AI-generated summary
This report introduces the Qwen2 series, the latest addition to our large language models and large multimodal models. We release a comprehensive suite of foundational and instruction-tuned language models, encompassing a parameter range from 0.5 to 72 billion, featuring dense models and a Mixture-of-Experts model. Qwen2 surpasses most prior open-weight models, including its predecessor Qwen1.5, and exhibits competitive performance relative to proprietary models across diverse benchmarks on language understanding, generation, multilingual proficiency, coding, mathematics, and reasoning. The flagship model, Qwen2-72B, showcases remarkable performance: 84.2 on MMLU, 37.9 on GPQA, 64.6 on HumanEval, 89.5 on GSM8K, and 82.4 on BBH as a base language model. The instruction-tuned variant, Qwen2-72B-Instruct, attains 9.1 on MT-Bench, 48.1 on Arena-Hard, and 35.7 on LiveCodeBench. Moreover, Qwen2 demonstrates robust multilingual capabilities, proficient in approximately 30 languages, spanning English, Chinese, Spanish, French, German, Arabic, Russian, Korean, Japanese, Thai, Vietnamese, and more, underscoring its versatility and global reach. To foster community innovation and accessibility, we have made the Qwen2 model weights openly available on Hugging Face1 and ModelScope2, and the supplementary materials including example code on GitHub3. These platforms also include resources for quantization, fine-tuning, and deployment, facilitating a wide range of applications and research endeavors.
Community
Qwen2 Technical Report
This is an automated message from the Librarian Bot. I found the following papers similar to this paper.
The following papers were recommended by the Semantic Scholar API
- YuLan: An Open-source Large Language Model (2024)
- GEB-1.3B: Open Lightweight Large Language Model (2024)
- A Teacher Is Worth A Million Instructions (2024)
- Aya 23: Open Weight Releases to Further Multilingual Progress (2024)
- A Survey on Large Language Models for Code Generation (2024)
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recommend