README.md

metadata

license: apache-2.0
tags:
  - merge
  - mergekit
base_model:
  - failspy/Llama-3-8B-Instruct-abliterated
model-index:
  - name: Aura-Llama-Abliterated
    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: 49.23
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-Llama-Abliterated
          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: 72.27
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-Llama-Abliterated
          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: 55.71
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-Llama-Abliterated
          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: 46.63
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-Llama-Abliterated
          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: 69.3
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-Llama-Abliterated
          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: 27.6
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TheSkullery/Aura-Llama-Abliterated
          name: Open LLM Leaderboard

Aura-llama-3-Abliterated

Now that the cute anime girl has your attention.

UPDATE: Model is now using the abliterated version of meta llama 3 8b

Aura-llama is using the methodology presented by SOLAR for scaling LLMs called depth up-scaling (DUS), which encompasses architectural modifications with continued pretraining. Using the solar paper as a base, I integrated Llama-3 weights into the upscaled layers, and In the future plan to continue training the model.

Aura-llama is a merge of the following models to create a base model to work from:

• failspy/Llama-3-8B-Instruct-abliterated
• failspy/Llama-3-8B-Instruct-abliterated

Abliterated Merged Evals (Has Not Been Finetuned):

Aura-llama-Abliterated

• Avg: ?
• ARC: ?
• HellaSwag: ?
• MMLU: ?
• T-QA: ?
• Winogrande: ?
• GSM8K: ?

Non Abliterated Merged Evals (Has Not Been Finetuned):

Aura-llama-Original

• Avg: 63.13
• ARC: 58.02
• HellaSwag: 77.82
• MMLU: 65.61
• T-QA: 51.94
• Winogrande: 73.40
• GSM8K: 52.01

🧩 Configuration

dtype: bfloat16
merge_method: passthrough
slices:
- sources:
  - layer_range: [0, 12]
    model: failspy/Llama-3-8B-Instruct-abliterated
- sources:
  - layer_range: [8, 20]
    model: failspy/Llama-3-8B-Instruct-abliterated
- sources:
  - layer_range: [16, 28]
    model: failspy/Llama-3-8B-Instruct-abliterated
- sources:
  - layer_range: [24, 32]
    model: failspy/Llama-3-8B-Instruct-abliterated
        

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	53.46
AI2 Reasoning Challenge (25-Shot)	49.23
HellaSwag (10-Shot)	72.27
MMLU (5-Shot)	55.71
TruthfulQA (0-shot)	46.63
Winogrande (5-shot)	69.30
GSM8k (5-shot)	27.60