README.md

metadata

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
• Merged Sources:
  • arcee-ai/Llama-3.1-SuperNova-Lite
  • deepseek-ai/DeepSeek-R1-Distill-Llama-8B
  • 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

Detailed results can be found here! Summarized results can be found here!

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