qwen

6 个模型尺寸，包括 0.5B、1.8B、4B（默认）、7B、14B、32B（新增）和 72B
- ollama run qwen:0.5b
- ollama run qwen:1.8b
- ollama run qwen:4b
- ollama run qwen:7b
- ollama run qwen:14b
- ollama run qwen:32b
- ollama run qwen:72b
- ollama run qwen:110b
在聊天模型的人类偏好方面显着提升性能
基础模型和聊天模型都支持多语言
所有尺寸模型稳定支持 32K 上下文长度

原始 Qwen 模型提供四种不同的参数尺寸：1.8B、7B、14B 和 72B。

特性

低成本部署：推理所需的最低内存小于 2GB。
大规模高质量训练语料库：模型在超过 2.2 万亿个词元的语料库上进行预训练，包括中文、英文、多语言文本、代码和数学，涵盖一般和专业领域。预训练语料库的分布已通过大量消融实验进行了优化。
良好的性能： Qwen 支持长上下文长度（1.8b、7b 和 14b 参数模型为 8K，72b 参数模型为 32K），并且在多个中文和英文下游评估任务（包括常识、推理、代码、数学等）上显著优于同等规模的现有开源模型，甚至在多个基准测试中超过了一些更大规模的模型。
更全面的词汇覆盖率：与基于中英文词汇库的其他开源模型相比，Qwen 使用超过 150K 个词元的词汇库。这个词汇库对多种语言更友好，使用户能够在不扩展词汇库的情况下直接进一步增强特定语言的能力。
系统提示： Qwen 可以通过使用系统提示来实现角色扮演、语言风格转换、任务设置和行为设置。

参考

GitHub

Hugging Face

Qwen 2 is now available [here](https://ollama.org.cn/library/qwen2).

Qwen is a series of transformer-based large language models by Alibaba Cloud, pre-trained on a large volume of data, including web texts, books, code, etc.

### New in Qwen 1.5

- 6 model sizes, including 0.5B, 1.8B, 4B (default), 7B, 14B, 32B (new) and 72B
  * `ollama run qwen:0.5b`
  * `ollama run qwen:1.8b`
  * `ollama run qwen:4b` 
  * `ollama run qwen:7b` 
  * `ollama run qwen:14b`
  * `ollama run qwen:32b`
  * `ollama run qwen:72b`
  * `ollama run qwen:110b`
- Significant performance improvement in human preference for chat models
- Multilingual support of both base and chat models
- Stable support of 32K context length for models of all sizes

The original Qwen model is offered in four different parameter sizes: 1.8B, 7B, 14B, and 72B.

## Features

* **Low-cost deployment**: the minimum memory requirement for inference is less than 2GB.

* **Large-scale high-quality training corpora**: Models are pre-trained on over 2.2 trillion tokens, including Chinese, English, multilingual texts, code, and mathematics, covering general and professional fields. The distribution of the pre-training corpus has been optimized through a large number of ablation experiments.

* **Good performance**: Qwen supports long context lengths (8K on the `1.8b`, `7b` and `14b` parameter models, and 32K on the `72b` parameter model), and significantly surpasses existing open-source models of similar scale on multiple Chinese and English downstream evaluation tasks (including common-sense, reasoning, code, mathematics, etc.), and even surpasses some larger-scale models in several benchmarks.

* **More comprehensive vocabulary coverage**: Compared with other open-source models based on Chinese and English vocabularies, Qwen uses a vocabulary of over 150K tokens. This vocabulary is more friendly to multiple languages, enabling users to directly further enhance the capability for certain languages without expanding the vocabulary.

* **System prompt**: Qwen can realize role playing, language style transfer, task setting, and behavior-setting by using a system prompt.

## Reference

[GitHub](https://github.com/QwenLM/Qwen)

[Hugging Face](https://hugging-face.cn/Qwen)

粘贴、拖放或点击上传图片（.png、.jpeg、.jpg、.svg、.gif）