--- 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 Data Card

Aura-llama-3-Abliterated

Aura-llama-Abliterated Image

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:

Abliterated Merged Evals (Has Not Been Finetuned):

Aura-llama-Abliterated

Non Abliterated Merged Evals (Has Not Been Finetuned):

Aura-llama-Original

🧩 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](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_TheSkullery__Aura-Llama-Abliterated) | 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|