---
license: other
pipeline_tag: text-generation
model-index:
- name: internlm2-math-20b-llama
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 59.98
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bartowski/internlm2-math-20b-llama
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 81.64
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bartowski/internlm2-math-20b-llama
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 65.07
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bartowski/internlm2-math-20b-llama
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 52.9
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bartowski/internlm2-math-20b-llama
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 76.4
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bartowski/internlm2-math-20b-llama
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 2.12
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=bartowski/internlm2-math-20b-llama
      name: Open LLM Leaderboard
---
# InternLM 

<div align="center">

<img src="https://github.com/InternLM/InternLM/assets/22529082/b9788105-8892-4398-8b47-b513a292378e" width="200"/>
  <div>&nbsp;</div>
  <div align="center">
    <b><font size="5">InternLM</font></b>
    <sup>
      <a href="https://internlm.intern-ai.org.cn/">
        <i><font size="4">HOT</font></i>
      </a>
    </sup>
    <div>&nbsp;</div>
  </div>
  
[![evaluation](https://github.com/InternLM/InternLM/assets/22529082/f80a2a58-5ddf-471a-8da4-32ab65c8fd3b)](https://github.com/internLM/OpenCompass/)

[💻Github Repo](https://github.com/InternLM/InternLM)

</div>


## Converted using <a href="https://huggingface.co/chargoddard">Charles Goddard's</a> conversion script to create llama models from internlm

Original REPO link: https://huggingface.co/internlm/internlm2-math-20b

ExLLamaV2 link: https://huggingface.co/bartowski/internlm2-math-20b-llama-exl2

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_bartowski__internlm2-math-20b-llama)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |56.35|
|AI2 Reasoning Challenge (25-Shot)|59.98|
|HellaSwag (10-Shot)              |81.64|
|MMLU (5-Shot)                    |65.07|
|TruthfulQA (0-shot)              |52.90|
|Winogrande (5-shot)              |76.40|
|GSM8k (5-shot)                   | 2.12|