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</details>
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<details>
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<summary>Shanghai AI Laboratory</summary>
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- [InternLM2-1.8|7|20B](https://huggingface.co/collections/internlm/internlm2-65b0ce04970888799707893c)
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- [InternLM-Math-7B|20B](https://huggingface.co/collections/internlm/internlm2-math-65b0ce88bf7d3327d0a5ad9f)
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- [InternLM-XComposer2-1.8|7B](https://huggingface.co/collections/internlm/internlm-xcomposer2-65b3706bf5d76208998e7477)
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- [InternVL-2|6|14|26](https://huggingface.co/collections/OpenGVLab/internvl-65b92d6be81c86166ca0dde4)
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</details>
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## LLM Data
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> Reference: [LLMDataHub](https://github.com/Zjh-819/LLMDataHub)
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- [IBM data-prep-kit](https://github.com/IBM/data-prep-kit) - Open-Source Toolkit for Efficient Unstructured Data Processing with Pre-built Modules and Local to Cluster Scalability.
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- [Datatrove](https://github.com/huggingface/datatrove) - Freeing data processing from scripting madness by providing a set of platform-agnostic customizable pipeline processing blocks.
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+- [Dingo](https://github.com/DataEval/dingo) - Dingo: A Comprehensive Data Quality Evaluation Tool
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## LLM Evaluation:
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- [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) - A framework for few-shot evaluation of language models.
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