---
license: apache-2.0
library_name: transformers
tags:
- merge
pipeline_tag: text-generation
model-index:
- name: TheTop-5x7B-Instruct-S4-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: 72.18
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S4-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: 88.29
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S4-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: 65.03
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S4-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: 65.56
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S4-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: 85.16
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S4-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: 73.39
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S4-v0.1
      name: Open LLM Leaderboard
---

Merge of top 7B models and the SLERP of other 7B models

> 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


![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fd5e18a90b6dc4633f6d292/3a2An3rpaLMusQrtQ74Up.png)


```python
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        "acc_stderr": 0.03199600851869088,
        "acc_norm": 0.6554901222242155,
        "acc_norm_stderr": 0.03267670432184765,
        "mc1": 0.5104039167686658,
        "mc1_stderr": 0.017499711430249268,
        "mc2": 0.6556430108444109,
        "mc2_stderr": 0.015519025079862213
    },
    "harness|arc:challenge|25": {
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        "acc_stderr": 0.013491429517292038,
        "acc_norm": 0.7218430034129693,
        "acc_norm_stderr": 0.013094469919538812
    },
    "harness|hellaswag|10": {
        "acc": 0.7202748456482773,
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        "acc_norm": 0.8828918542123083,
        "acc_norm_stderr": 0.003208919510309931
    },
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    },
    "harness|hendrycksTest-anatomy|5": {
        "acc": 0.6518518518518519,
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        "acc_norm": 0.6518518518518519,
        "acc_norm_stderr": 0.041153246103369526
    },
    "harness|hendrycksTest-astronomy|5": {
        "acc": 0.7039473684210527,
        "acc_stderr": 0.03715062154998904,
        "acc_norm": 0.7039473684210527,
        "acc_norm_stderr": 0.03715062154998904
    },
    "harness|hendrycksTest-business_ethics|5": {
        "acc": 0.66,
        "acc_stderr": 0.04760952285695238,
        "acc_norm": 0.66,
        "acc_norm_stderr": 0.04760952285695238
    },
    "harness|hendrycksTest-clinical_knowledge|5": {
        "acc": 0.6981132075471698,
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    },
    "harness|hendrycksTest-college_biology|5": {
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    "harness|hendrycksTest-college_chemistry|5": {
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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_macroeconomics|5": {
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    "harness|hendrycksTest-high_school_microeconomics|5": {
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    "harness|hendrycksTest-high_school_physics|5": {
        "acc": 0.36423841059602646,
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    },
    "harness|hendrycksTest-high_school_psychology|5": {
        "acc": 0.8366972477064221,
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    "harness|hendrycksTest-high_school_statistics|5": {
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    "harness|hendrycksTest-high_school_us_history|5": {
        "acc": 0.8529411764705882,
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    "harness|hendrycksTest-high_school_world_history|5": {
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    "harness|hendrycksTest-human_aging|5": {
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    "harness|hendrycksTest-human_sexuality|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-professional_accounting|5": {
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    "harness|hendrycksTest-security_studies|5": {
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    "harness|hendrycksTest-sociology|5": {
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    "harness|hendrycksTest-world_religions|5": {
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    },
    "harness|truthfulqa:mc|0": {
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        "acc": 0.8516179952644041,
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    "harness|gsm8k|5": {
        "acc": 0.7338893100833965,
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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-S4-v0.1)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |74.94|
|AI2 Reasoning Challenge (25-Shot)|72.18|
|HellaSwag (10-Shot)              |88.29|
|MMLU (5-Shot)                    |65.03|
|TruthfulQA (0-shot)              |65.56|
|Winogrande (5-shot)              |85.16|
|GSM8k (5-shot)                   |73.39|