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Model: gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES Source: Original Platform
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README.md
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README.md
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---
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license: llama3.1
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library_name: transformers
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tags:
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- mergekit
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- merge
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base_model:
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- mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
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- meta-llama/Meta-Llama-3.1-8B
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- meta-llama/Meta-Llama-3.1-8B-Instruct
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model-index:
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- name: Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 45.51
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name: strict accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 28.91
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 11.63
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name: exact match
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 2.24
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 6.59
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 29.76
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES
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name: Open LLM Leaderboard
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---
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# Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) as a base.
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### Models Merged
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The following models were included in the merge:
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* [mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated](https://huggingface.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated)
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* [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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base_model: meta-llama/Meta-Llama-3.1-8B
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chat_template: auto
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dtype: float16
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merge_method: ties
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models:
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- model: mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
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parameters:
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density: 0.5
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weight: 0.5
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- model: meta-llama/Meta-Llama-3.1-8B-Instruct
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parameters:
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density: 0.5
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weight: 0.5
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parameters:
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int8_mask: true
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normalize: false
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_gaverfraxz__Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |20.77|
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|IFEval (0-Shot) |45.51|
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|BBH (3-Shot) |28.91|
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|MATH Lvl 5 (4-Shot)|11.63|
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|GPQA (0-shot) | 2.24|
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|MuSR (0-shot) | 6.59|
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|MMLU-PRO (5-shot) |29.76|
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