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reformat open llm leaderboard and add buy me a cofee link
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metadata
license: apache-2.0
tags:
  - mistral
datasets:
  - Open-Orca/SlimOrca
model-index:
  - name: OpenHermes-2.5-neural-chat-7b-v3-2-7B
    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: 66.38
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/OpenHermes-2.5-neural-chat-7b-v3-2-7B
          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: 84.11
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/OpenHermes-2.5-neural-chat-7b-v3-2-7B
          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: 62.84
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/OpenHermes-2.5-neural-chat-7b-v3-2-7B
          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: 63.59
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/OpenHermes-2.5-neural-chat-7b-v3-2-7B
          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: 78.53
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/OpenHermes-2.5-neural-chat-7b-v3-2-7B
          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: 56.79
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/OpenHermes-2.5-neural-chat-7b-v3-2-7B
          name: Open LLM Leaderboard

image/png

Merge of teknium/OpenHermes-2.5-Mistral-7B and Intel/neural-chat-7b-v3-2 using ties merge.

Note: Intel/neural-chat-7b-v3-1 merge version is available here

Weights

Density

Prompt Templates

You can use these prompt templates, but I recommend using ChatML.

ChatML (OpenHermes-2.5-Mistral-7B):

<|im_start|>system
{system}<|im_end|>
<|im_start|>user
{user}<|im_end|>
<|im_start|>assistant
{asistant}<|im_end|>

neural-chat-7b-v3-2:

### System:
{system}
### User:
{user}
### Assistant:

Quantizationed versions

Quantizationed versions of this model is available thanks to TheBloke.

GPTQ
GGUF
AWQ

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 68.71
AI2 Reasoning Challenge (25-Shot) 66.38
HellaSwag (10-Shot) 84.11
MMLU (5-Shot) 62.84
TruthfulQA (0-shot) 63.59
Winogrande (5-shot) 78.53
GSM8k (5-shot) 56.79

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