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--- |
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license: llama3 |
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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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- failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 |
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model-index: |
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- name: AbL3In-15B |
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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: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 61.77 |
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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=TheSkullery/AbL3In-15B |
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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: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 78.42 |
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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=TheSkullery/AbL3In-15B |
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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 (5-Shot) |
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type: cais/mmlu |
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config: all |
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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: 66.57 |
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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=TheSkullery/AbL3In-15B |
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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: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 52.53 |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=TheSkullery/AbL3In-15B |
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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: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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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: 74.74 |
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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=TheSkullery/AbL3In-15B |
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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: GSM8k (5-shot) |
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type: gsm8k |
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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: 70.74 |
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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=TheSkullery/AbL3In-15B |
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name: Open LLM Leaderboard |
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--- |
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# merge |
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This is a testing model using the zeroing method used by [elinas/Llama-3-15B-Instruct-zeroed](https://huggingface.co/elinas/Llama-3-15B-Instruct-zeroed). |
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If this model pans out in the way I hope, Ill heal it then reupload with a custom model card like the others. currently this is just an experiment. |
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In case anyone asks AbL3In-15b literally means: |
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```yaml |
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Ab = Abliterated |
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L3 = Llama-3 |
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In = Instruct |
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15b = its 15b perameters |
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``` |
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## GGUF's |
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[GGUF by @Mradermacher](https://huggingface.co/mradermacher/AbL3In-15B-GGUF) |
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## Merge Details |
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### Merge Method |
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This model was merged using the passthrough merge method. |
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### Models Merged |
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The following models were included in the merge: |
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* [failspy/Meta-Llama-3-8B-Instruct-abliterated-v3](https://huggingface.co/failspy/Meta-Llama-3-8B-Instruct-abliterated-v3) |
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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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dtype: bfloat16 |
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merge_method: passthrough |
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slices: |
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- sources: |
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- layer_range: [0, 24] |
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model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 |
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- sources: |
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- layer_range: [8, 24] |
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model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 |
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parameters: |
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scale: |
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- filter: o_proj |
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value: 0.0 |
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- filter: down_proj |
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value: 0.0 |
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- value: 1.0 |
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- sources: |
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- layer_range: [8, 24] |
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model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 |
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parameters: |
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scale: |
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- filter: o_proj |
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value: 0.0 |
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- filter: down_proj |
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value: 0.0 |
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- value: 1.0 |
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- sources: |
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- layer_range: [24, 32] |
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model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 |
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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_TheSkullery__AbL3In-15B) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |67.46| |
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|AI2 Reasoning Challenge (25-Shot)|61.77| |
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|HellaSwag (10-Shot) |78.42| |
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|MMLU (5-Shot) |66.57| |
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|TruthfulQA (0-shot) |52.53| |
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|Winogrande (5-shot) |74.74| |
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|GSM8k (5-shot) |70.74| |
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