Mistral
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MistralAI-based models
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Merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
A merge of some of my fave Mistral Nemo models.
Quant: https://huggingface.co/Triangle104/Annunaki-12b-Q4_K_M-GGUF
Merge Method
This model was merged using the Model Stock merge method using nothingiisreal/MN-12B-Celeste-V1.9 as a base.
Models Merged
The following models were included in the merge:
- elinas/Chronos-Gold-12B-1.0
- nbeerbower/mistral-nemo-gutenberg3-12B
- crestf411/MN-Slush
- Gryphe/Pantheon-RP-1.6.1-12b-Nemo
- anthracite-org/magnum-v4-12b
Configuration
The following YAML configuration was used to produce this model:
models:
- model: crestf411/MN-Slush
- model: elinas/Chronos-Gold-12B-1.0
- model: nbeerbower/mistral-nemo-gutenberg3-12B
- model: nothingiisreal/MN-12B-Celeste-V1.9
- model: anthracite-org/magnum-v4-12b
- model: Gryphe/Pantheon-RP-1.6.1-12b-Nemo
base_model: nothingiisreal/MN-12B-Celeste-V1.9
merge_method: model_stock
parameters:
normalize: true
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 23.23 |
| IFEval (0-Shot) | 38.72 |
| BBH (3-Shot) | 35.32 |
| MATH Lvl 5 (4-Shot) | 11.33 |
| GPQA (0-shot) | 9.51 |
| MuSR (0-shot) | 14.28 |
| MMLU-PRO (5-shot) | 30.23 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard38.720
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard35.320
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard11.330
- acc_norm on GPQA (0-shot)Open LLM Leaderboard9.510
- acc_norm on MuSR (0-shot)Open LLM Leaderboard14.280
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard30.230