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README.md
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<b><font size="6">
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## Models
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- [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.
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- [InternLM](https://github.com/InternLM/InternLM): a series of multi-lingual foundation models and chat models.
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- [InternLM-Math](https://github.com/InternLM/InternLM-Math): state-of-the-art bilingual math reasoning LLMs.
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## Toolchain
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- [InternEvo](https://github.com/InternLM/InternEvo/): a lightweight framework for large-scale model pre-training and finetuning.
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- [XTuner](https://github.com/InternLM/xtuner): a toolkit for efficiently fine-tuning LLMs, supporting various models and fintuning algorithms.
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- [LMDeploy](https://github.com/InternLM/lmdeploy): a toolkit for compressing, deploying, and serving LLMs.
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- [Lagent](https://github.com/InternLM/lagent): a lightweight framework that allows users to efficiently build LLM-based agents.
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- [AgentLego](https://github.com/InternLM/agentlego): a library of versatile tool APIs to extend and enhance LLM-based agents, compatible with Lagent, Langchain, etc.
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- [OpenCompass](https://github.com/open-compass/opencompass): a platform for large model evaluation, providing a fair, open, and reproducible benchmark.
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- [OpenAOE](https://github.com/InternLM/OpenAOE): an elegant and out-of-the-box chat UI for comparing mulitple models.
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## Applications
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- [HuixiangDou](https://github.com/InternLM/HuixiangDou): a domain-specific assistant based on LLMs which can deal with complex techinical questions in group chats.
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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.
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## Models
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- [InternVL](https://github.com/OpenGVLab/InternVL): an advanced multimodal large language model (MLLM) series that demonstrates superior overall performance.
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- [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.
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- [InternLM](https://github.com/InternLM/InternLM): a series of multi-lingual foundation models and chat models.
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- [InternLM-Math](https://github.com/InternLM/InternLM-Math): state-of-the-art bilingual math reasoning LLMs.
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## Toolchain
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- [XTuner](https://github.com/InternLM/xtuner): a toolkit for efficiently fine-tuning LLMs, supporting various models and fintuning algorithms.
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- [LMDeploy](https://github.com/InternLM/lmdeploy): a toolkit for compressing, deploying, and serving LLMs.
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- [Lagent](https://github.com/InternLM/lagent): a lightweight framework that allows users to efficiently build LLM-based agents.
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- [OpenCompass](https://github.com/open-compass/opencompass): a platform for large model evaluation, providing a fair, open, and reproducible benchmark.
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