---
language:
- en
license: apache-2.0
model-index:
- name: supermario-v1
  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: 27.73
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
      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: 25.83
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
      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: 27.04
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
      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: 47.27
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
      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: 49.09
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
      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: 0.0
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=janhq/supermario-v1
      name: Open LLM Leaderboard
---
<!-- header start -->
<!-- 200823 -->

<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://github.com/janhq/jan/assets/89722390/35daac7d-b895-487c-a6ac-6663daaad78e" alt="Jan banner" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>

<p align="center">
    <a href="https://jan.ai/">Jan</a> 
    - <a href="https://discord.gg/AsJ8krTT3N">Discord</a>
</p>
<!-- header end -->

# Model Description
This model uses the `DARE_TIES` merge method.

**NOTE:** Due to the mismatch of architecture between Llama and Mistral, Magicoder-S-CL-7B layers will be skipped

```yaml
base_model: mistralai/Mistral-7B-v0.1
dtype: bfloat16
merge_method: dare_ties
models:
- model: mistralai/Mistral-7B-v0.1
- model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
  parameters:
    density: 0.8
    weight: 0.3
- model: Q-bert/MetaMath-Cybertron-Starling
  parameters:
    density: 0.8
    weight: 0.3
- model: ise-uiuc/Magicoder-S-CL-7B
  parameters:
    density: 0.6
    weight: 0.2
- model: AIDC-ai-business/Marcoroni-7B-v3
  parameters:
    density: 0.6
    weight: 0.2
parameters:
  int8_mask: true
```

# Run this model
You can run this model using [Jan Desktop](https://jan.ai/) on Mac, Windows, or Linux.

Jan is an open source, ChatGPT alternative that is:

- 💻  **100% offline on your machine**: Your conversations remain confidential, and visible only to you.
- 🗂️ **An Open File Format**: Conversations and model settings stay on your computer and can be exported or deleted at any time.
- 🌐 **OpenAI Compatible**: Local server on port `1337` with OpenAI compatible endpoints
- 🌍 **Open Source & Free**: We build in public; check out our [Github](https://github.com/janhq)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/r7VmEBLGXpPLTu2MImM7S.png)

# About Jan
Jan believes in the need for an open-source AI ecosystem and is building the infra and tooling to allow open-source AIs to compete on a level playing field with proprietary ones.

Jan's long-term vision is to build a cognitive framework for future robots, who are practical, useful assistants for humans and businesses in everyday life.

# Jan Model Merger
This is a test project for merging models.

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)

Detailed results can be found here.

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | ?|
| ARC (25-shot)         | ?          |
| HellaSwag (10-shot)   | ?   |
| MMLU (5-shot)         | ?|
| TruthfulQA (0-shot)   | ? |
| Winogrande (5-shot)   | ?  |
| GSM8K (5-shot)        | ?        |

# Acknowlegement
- [mergekit](https://github.com/cg123/mergekit)
- [DARE](https://github.com/yule-BUAA/MergeLM/blob/main/README.md)
- [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness)
# [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_janhq__supermario-v1)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |29.49|
|AI2 Reasoning Challenge (25-Shot)|27.73|
|HellaSwag (10-Shot)              |25.83|
|MMLU (5-Shot)                    |27.04|
|TruthfulQA (0-shot)              |47.27|
|Winogrande (5-shot)              |49.09|
|GSM8k (5-shot)                   | 0.00|