Llama3.1-SuperDeepFuse/README.md

---
base_model:
- arcee-ai/Llama-3.1-SuperNova-Lite
- deepseek-ai/DeepSeek-R1-Distill-Llama-8B
- FuseAI/FuseChat-Llama-3.1-8B-Instruct
library_name: transformers
tags:
- mergekit
- merge
license: llama3.1
language:
- en
model-index:
- name: Llama3.1-SuperDeepFuse
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: wis-k/instruction-following-eval
      split: train
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 77.62
      name: averaged accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-SuperDeepFuse
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: SaylorTwift/bbh
      split: test
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 29.22
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-SuperDeepFuse
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: lighteval/MATH-Hard
      split: test
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 17.75
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-SuperDeepFuse
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      split: train
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 3.24
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-SuperDeepFuse
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MuSR (0-shot)
      type: TAUR-Lab/MuSR
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 5.13
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-SuperDeepFuse
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU-PRO (5-shot)
      type: TIGER-Lab/MMLU-Pro
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 30.83
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-SuperDeepFuse
      name: Open LLM Leaderboard
---
# Llama3.1-SuperDeepFuse

An 8B parameter language model that merges three high-performance distilled models to boost reasoning, instruction-following, and performance in mathematics and coding.

## Model Highlights

- **Size**: 8 billion parameters
- **Base**: [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct)
- **Merged Sources**:
  - [arcee-ai/Llama-3.1-**Super**Nova-Lite](https://huggingface.co/arcee-ai/Llama-3.1-SuperNova-Lite)
  - [deepseek-ai/**Deep**Seek-R1-Distill-Llama-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B)
  - [FuseAI/**Fuse**Chat-Llama-3.1-8B-Instruct](https://huggingface.co/FuseAI/FuseChat-Llama-3.1-8B-Instruct)
- **Merge Method**: `model_stock`

## Key Capabilities

- Enhanced multi-task reasoning
- Improved mathematical and coding performance
- Multilingual support

## Performance Notes

- Maintains Llama 3.1 safety standards
- Suitable for consumer GPU deployment
- Balanced performance across diverse tasks

## Considerations

- Still being benchmarked
- Capabilities limited compared to larger model variants
- Can give misleading output like all other language models
- Outputs should be independently verified

## Licensing

Follows standard Llama 3.1 usage terms.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/agentlans__Llama3.1-SuperDeepFuse-details)!
Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=agentlans%2FLlama3.1-SuperDeepFuse&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!

|      Metric       |Value (%)|
|-------------------|--------:|
|**Average**        |    27.30|
|IFEval (0-Shot)    |    77.62|
|BBH (3-Shot)       |    29.22|
|MATH Lvl 5 (4-Shot)|    17.75|
|GPQA (0-shot)      |     3.24|
|MuSR (0-shot)      |     5.13|
|MMLU-PRO (5-shot)  |    30.83|