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InternLM-7B Model Card

Introduction

InternLM-7B contains 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.

Model Zoo

Model Transformers(HF) ModelScope(HF) OpenXLab(HF) OpenXLab(Original) Release Date
InternLM Chat 7B 🤗internlm/internlm-chat-7b Shanghai_AI_Laboratory/internlm-chat-7b Open in OpenXLab Open in OpenXLab 2023-12-12
InternLM 7B 🤗internlm/internlm-7b Shanghai_AI_Laboratory/internlm-7b Open in OpenXLab Open in OpenXLab 2023-07-06

Performance Evaluation

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.

Datasets\Models InternLM-Chat-7B InternLM-7B LLaMA-7B Baichuan-7B ChatGLM2-6B Alpaca-7B Vicuna-7B
C-Eval(Val) 52.0 53.4 24.2 42.7 50.9 28.9 31.2
MMLU 52.6 51.0 35.2* 41.5 46.0 39.7 47.3
AGIEval 46.4 37.6 20.8 24.6 39.0 24.1 26.4
CommonSenseQA 80.8 59.5 65.0 58.8 60.0 68.7 66.7
BUSTM 80.6 50.6 48.5 51.3 55.0 48.8 62.5
CLUEWSC 81.8 59.1 50.3 52.8 59.8 50.3 52.2
MATH 5.0 7.1 2.8 3.0 6.6 2.2 2.8
GSM8K 36.2 31.2 10.1 9.7 29.2 6.0 15.3
HumanEval 15.9 10.4 14.0 9.2 9.2 9.2 11.0
RACE(High) 80.3 57.4 46.9* 28.1 66.3 40.7 54.0
  • 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.