---
license: apache-2.0
library_name: transformers
tags:
- merge
pipeline_tag: text-generation
model-index:
- name: TheTop-5x7B-Instruct-S2-v0.1
  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: 69.45
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S2-v0.1
      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: 87.15
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S2-v0.1
      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: 64.98
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S2-v0.1
      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: 62.18
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S2-v0.1
      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: 79.64
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S2-v0.1
      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: 72.02
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S2-v0.1
      name: Open LLM Leaderboard
---

# MaziyarPanahi/TheTop-5x7B-Instruct-S2-v0.1

Merge of top 7B models with SLERP method.

> mergekit is a toolkit for merging pre-trained language models. mergekit uses an out-of-core approach to perform unreasonably elaborate merges in resource-constrained situations. Merges can be run entirely on CPU or accelerated with as little as 8 GB of VRAM. Many merging algorithms are supported, with more coming as they catch my attention.
>
> ## Eval
> ```python
> {
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        "acc_norm": 0.6542757501692061,
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        "mc1": 0.45165238678090575,
        "mc1_stderr": 0.017421480300277643,
        "mc2": 0.6217500644350165,
        "mc2_stderr": 0.015583825644663436
    },
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        "acc": 0.6723549488054608,
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        "acc_norm": 0.6945392491467577,
        "acc_norm_stderr": 0.01346008047800251
    },
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        "acc": 0.7046405098585939,
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        "acc_norm": 0.871539533957379,
        "acc_norm_stderr": 0.0033391798350182853
    },
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    },
    "harness|hendrycksTest-anatomy|5": {
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        "acc_norm": 0.6148148148148148,
        "acc_norm_stderr": 0.04203921040156279
    },
    "harness|hendrycksTest-astronomy|5": {
        "acc": 0.6907894736842105,
        "acc_stderr": 0.037610708698674805,
        "acc_norm": 0.6907894736842105,
        "acc_norm_stderr": 0.037610708698674805
    },
    "harness|hendrycksTest-business_ethics|5": {
        "acc": 0.63,
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        "acc_norm": 0.63,
        "acc_norm_stderr": 0.04852365870939099
    },
    "harness|hendrycksTest-clinical_knowledge|5": {
        "acc": 0.7132075471698113,
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    "harness|hendrycksTest-college_biology|5": {
        "acc": 0.7638888888888888,
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        "acc": 0.47,
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    "harness|hendrycksTest-college_computer_science|5": {
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    "harness|hendrycksTest-computer_security|5": {
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    "harness|hendrycksTest-high_school_biology|5": {
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        "acc": 0.6717948717948717,
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    "harness|hendrycksTest-high_school_microeconomics|5": {
        "acc": 0.6638655462184874,
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    "harness|hendrycksTest-high_school_physics|5": {
        "acc": 0.304635761589404,
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        "acc_norm": 0.304635761589404,
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    "harness|hendrycksTest-high_school_psychology|5": {
        "acc": 0.8458715596330275,
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    "harness|hendrycksTest-high_school_statistics|5": {
        "acc": 0.5185185185185185,
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        "acc_norm": 0.5185185185185185,
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    "harness|hendrycksTest-high_school_us_history|5": {
        "acc": 0.8382352941176471,
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    "harness|hendrycksTest-high_school_world_history|5": {
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    "harness|hendrycksTest-human_aging|5": {
        "acc": 0.6905829596412556,
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    "harness|hendrycksTest-human_sexuality|5": {
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    "harness|hendrycksTest-international_law|5": {
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    "harness|hendrycksTest-management|5": {
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    "harness|hendrycksTest-marketing|5": {
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    "harness|hendrycksTest-medical_genetics|5": {
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    "harness|hendrycksTest-miscellaneous|5": {
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    "harness|hendrycksTest-moral_disputes|5": {
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    "harness|hendrycksTest-world_religions|5": {
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    "harness|truthfulqa:mc|0": {
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        "mc2": 0.6217500644350165,
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    "harness|winogrande|5": {
        "acc": 0.7963693764798737,
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    "harness|gsm8k|5": {
        "acc": 0.7202426080363912,
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    }
}
```

# [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_MaziyarPanahi__TheTop-5x7B-Instruct-S2-v0.1)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |72.57|
|AI2 Reasoning Challenge (25-Shot)|69.45|
|HellaSwag (10-Shot)              |87.15|
|MMLU (5-Shot)                    |64.98|
|TruthfulQA (0-shot)              |62.18|
|Winogrande (5-shot)              |79.64|
|GSM8k (5-shot)                   |72.02|