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Qwen2

Categories: Coding & Developer Tools, Chatbots & Assistants, Research  |  Pricing: Free  |  Official Website ↗

Qwen2 is a series of open-source large language models (LLMs) with various sizes, offering enhanced performance in coding, mathematics, and multilingual understanding.

Qwen2 represents an evolution from Qwen1.5, introducing pretrained and instruction-tuned models in five sizes: Qwen2-0.5B, Qwen2-1.5B, Qwen2-7B, Qwen2-57B-A14B, and Qwen2-72B. These models have been trained on data in 27 additional languages beyond English and Chinese, demonstrating state-of-the-art performance across numerous benchmark evaluations. Key improvements include significantly enhanced capabilities in coding and mathematics, and extended context length support up to 128K tokens for Qwen2-7B-Instruct and Qwen2-72B-Instruct. The models are open-sourced on Hugging Face and ModelScope, with licenses varying by model size; Qwen2-72B and its instruction-tuned models use the Qianwen License, while others adopt Apache 2.0. Qwen2-72B, in particular, shows superior performance compared to leading models like Llama-3-70B and its predecessor, Qwen1.5-110B, despite having fewer parameters. The development focused on augmenting both the volume and quality of pretraining and instruction-tuning datasets across a diverse linguistic spectrum, and addressing code-switching phenomena in multilingual evaluations. Post-training processes further refine the models' intelligence, aligning outputs with human values (helpful, honest, harmless) through automated alignment strategies like rejection sampling for math and execution feedback for coding. The models also demonstrate strong safety performance across various multilingual unsafe query categories, comparable to GPT-4 in some aspects. Future plans include training larger Qwen2 models and extending them to multimodal capabilities, understanding both vision and audio information.

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Integrations: Hugging Face, ModelScope, Axolotl, Llama-Factory, Firefly, Swift, XTuner, AutoGPTQ, AutoAWQ, Neural Compressor

Platforms: Web

Watch demo on YouTube ↗


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