Llama-3.1-8B-Instruct-abliterated_via_adapter
This model is a merge of pre-trained language models created using mergekit.
A LoRA was applied to "abliterate" refusals in meta-llama/Meta-Llama-3.1-8B-Instruct. The result appears to work despite the LoRA having been derived from Llama 3 instead of Llama 3.1, which implies that there is significant feature commonality between the 3 and 3.1 models.
The LoRA was extracted from failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 using meta-llama/Meta-Llama-3-8B-Instruct as a base.
Built with Llama.
Merge Details
Merge Method
This model was merged using the task arithmetic merge method using meta-llama/Meta-Llama-3.1-8B-Instruct + grimjim/Llama-3-Instruct-abliteration-LoRA-8B as a base.
Configuration
The following YAML configuration was used to produce this model:
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
dtype: bfloat16
merge_method: task_arithmetic
parameters:
normalize: false
slices:
- sources:
- layer_range: [0, 32]
model: meta-llama/Meta-Llama-3.1-8B-Instruct+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
parameters:
weight: 1.0
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 22.95 |
IFEval (0-Shot) | 48.70 |
BBH (3-Shot) | 29.42 |
MATH Lvl 5 (4-Shot) | 12.39 |
GPQA (0-shot) | 8.50 |
MuSR (0-shot) | 9.26 |
MMLU-PRO (5-shot) | 29.46 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard48.700
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard29.420
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard12.390
- acc_norm on GPQA (0-shot)Open LLM Leaderboard8.500
- acc_norm on MuSR (0-shot)Open LLM Leaderboard9.260
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard29.460