saishf/Neural-SOVLish-Devil-8B-L3

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

This is another "SOVL" style merge, this time using mlabonne/NeuralDaredevil-8B-abliterated.

Daredevil is the first abliterated model series i've tried that feels as smart as base llama-3-instruct while also being willing to give instructions to do all kinda of illegal things

Neural daredevil is trained further on the original abliterated model, which should result in a better experience in most scenarios. (A bandaid for the damage abliteration causes)

This model should do well in rp, I'm yet to test it (waiting for gguf files @_@)

Merge Method

This model was merged using the Model Stock merge method using mlabonne/NeuralDaredevil-8B-abliterated as a base.

Models Merged

The following models were included in the merge:

• mlabonne/NeuralDaredevil-8B-abliterated + ResplendentAI/BlueMoon_Llama3
• mlabonne/NeuralDaredevil-8B-abliterated + ResplendentAI/Smarts_Llama3
• mlabonne/NeuralDaredevil-8B-abliterated + ResplendentAI/Luna_Llama3
• mlabonne/NeuralDaredevil-8B-abliterated + ResplendentAI/Aura_Llama3
• mlabonne/NeuralDaredevil-8B-abliterated + ResplendentAI/RP_Format_QuoteAsterisk_Llama3

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: mlabonne/NeuralDaredevil-8B-abliterated+ResplendentAI/Aura_Llama3
  - model: mlabonne/NeuralDaredevil-8B-abliterated+ResplendentAI/Smarts_Llama3
  - model: mlabonne/NeuralDaredevil-8B-abliterated+ResplendentAI/Luna_Llama3
  - model: mlabonne/NeuralDaredevil-8B-abliterated+ResplendentAI/BlueMoon_Llama3
  - model: mlabonne/NeuralDaredevil-8B-abliterated+ResplendentAI/RP_Format_QuoteAsterisk_Llama3
merge_method: model_stock
base_model: mlabonne/NeuralDaredevil-8B-abliterated
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	72.22
AI2 Reasoning Challenge (25-Shot)	69.11
HellaSwag (10-Shot)	84.77
MMLU (5-Shot)	69.02
TruthfulQA (0-shot)	59.05
Winogrande (5-shot)	78.30
GSM8k (5-shot)	73.09