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title: README
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<b><font size="6">Intern Large Models</font></b>
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Intern-series large models are developed by Shanghai AI Laboratory. We keep open-sourcing high quality LLMs/MLLMs as well as a full-stack toolchain for development and application.
## Models
- [InternVL](https://github.com/OpenGVLab/InternVL): an advanced multimodal large language model (MLLM) series that demonstrates superior overall performance.
- [Intern-S1](https://github.com/InternLM/Intern-S1): a scientific multimodal large model with both strong general capabilities and the SOTA performance on various scientific tasks.
- [InternLM](https://github.com/InternLM/InternLM): a series of multi-lingual foundation models and chat models.
- [InternLM-Math](https://github.com/InternLM/InternLM-Math): state-of-the-art bilingual math reasoning LLMs.
- [InternLM-XComposer](https://github.com/InternLM/InternLM-XComposer): a vision-language large model (VLLM) based on InternLM for advanced text-image comprehension and composition.
## Toolchain
- [XTuner](https://github.com/InternLM/xtuner): a toolkit for efficiently fine-tuning LLMs, supporting various models and fintuning algorithms.
- [LMDeploy](https://github.com/InternLM/lmdeploy): a toolkit for compressing, deploying, and serving LLMs.
- [Lagent](https://github.com/InternLM/lagent): a lightweight framework that allows users to efficiently build LLM-based agents.
- [OpenCompass](https://github.com/open-compass/opencompass): a platform for large model evaluation, providing a fair, open, and reproducible benchmark.
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