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Qwen2.5 is a series of large language models developed by the Qwen team at Alibaba Cloud, designed to enhance natural language understanding and generation across multiple languages. The models are available in various sizes, including 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B parameters, catering to diverse computational requirements. Trained on a comprehensive dataset of up to 18 trillion tokens, Qwen2.5 models exhibit significant improvements in instruction following, long-text generation (exceeding 8,000 tokens), and structured data comprehension, such as tables and JSON formats. They support context lengths up to 128,000 tokens and offer multilingual capabilities in over 29 languages, including Chinese, English, French, Spanish, and more. The models are open-source under the Apache 2.0 license, with resources and documentation available on platforms like Hugging Face and ModelScope.
This is a full ZIP snapshot of the Qwen2.5 code.
Features
- Diverse Model Sizes: Available in 0.5B to 72B parameters, accommodating various computational needs.
- Extensive Training Data: Trained on up to 18 trillion tokens for comprehensive language understanding.
- Enhanced Instruction Following: Improved adherence to user instructions for accurate responses.
- Long-Text Generation: Capable of generating texts exceeding 8,000 tokens.
- Structured Data Comprehension: Proficient in understanding and generating structured outputs, including JSON.
- Extended Context Length: Supports context lengths up to 128,000 tokens for better context retention.
- Multilingual Support: Fluent in over 29 languages, broadening accessibility.
- Open-Source Availability: Released under the Apache 2.0 license, fostering community collaboration.
License
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User Reviews
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Great open source model series
