Mahou-1.5-mistral-nemo-12B-lorablated
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the task arithmetic merge method using flammenai/Mahou-1.5-mistral-nemo-12B + nbeerbower/Mistral-Nemo-12B-abliterated-LORA as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
base_model: flammenai/Mahou-1.5-mistral-nemo-12B+nbeerbower/Mistral-Nemo-12B-abliterated-LORA
dtype: bfloat16
merge_method: task_arithmetic
parameters:
normalize: false
slices:
- sources:
- layer_range: [0, 40]
model: flammenai/Mahou-1.5-mistral-nemo-12B+nbeerbower/Mistral-Nemo-12B-abliterated-LORA
parameters:
weight: 1.0
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 26.45 |
IFEval (0-Shot) | 68.25 |
BBH (3-Shot) | 36.08 |
MATH Lvl 5 (4-Shot) | 5.29 |
GPQA (0-shot) | 3.91 |
MuSR (0-shot) | 16.55 |
MMLU-PRO (5-shot) | 28.60 |
- Downloads last month
- 143
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for nbeerbower/Mahou-1.5-mistral-nemo-12B-lorablated
Merge model
this model
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard68.250
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard36.080
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard5.290
- acc_norm on GPQA (0-shot)Open LLM Leaderboard3.910
- acc_norm on MuSR (0-shot)Open LLM Leaderboard16.550
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard28.600