InternLM has open-sourced a 7 billion parameter base model and a chat model tailored for practical scenarios. The model has the following characteristics: - It leverages trillions of high-quality tokens for training to establish a powerful knowledge base. - It supports an 8k context window length, enabling longer input sequences and stronger reasoning capabilities. - It provides a versatile toolset for users to flexibly build their own workflows. We conducted a comprehensive evaluation of InternLM using the open-source evaluation tool OpenCompass. The evaluation covered five dimensions of capabilities: disciplinary competence, language competence, knowledge competence, inference competence, and comprehension competence. Here are some of the evaluation results, and you can visit the OpenCompass leaderboard for more evaluation results. - The evaluation results were obtained from OpenCompass 20230706 (some data marked with *, which means come from the original papers), and evaluation configuration can be found in the configuration files provided by OpenCompass. - The evaluation data may have numerical differences due to the version iteration of OpenCompass, so please refer to the latest evaluation results of OpenCompass.

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internlm-xcomposer-7b

internlm

**InternLM-XComposer** is a vision-language large model (VLLM) based on InternLM for advanced text-image comprehension and composition. InternLM-XComposer has serveal appealing properties: 1. **Text Generation**: It crafts long-form text based on human-provided instructions. 2. **Image Spoting and Captioning**: It pinpoints optimal locations for image placement and furnishes image descriptions. 3. **Image Retrieval and Selection**: It select image candidates and identify the image that optimally complements the content.

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internlm-xcomposer-7b-4bit

internlm

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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埋め込みと類似度

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internlm-xcomposer-vl-7b

internlm

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internlm-xcomposer2-4khd-7b

internlm

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画像質問応答

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internlm-xcomposer2-7b

internlm

**InternLM-XComposer2** is a vision-language large model (VLLM) based on InternLM2 for advanced text-image comprehension and composition. The code is licensed under Apache-2.0, while model weights are fully open for academic research and also allow free commercial usage. To apply for a commercial license, please fill in the application form (English)/申请表（中文）. For other questions or collaborations, please contact internlm@pjlab.org.cn.

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