--- base_model: - Qwen/Qwen2.5-7B-Instruct - Aashraf995/Qwen-Evo-7B - jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0 - Goekdeniz-Guelmez/Josiefied-Qwen2.5-7B-Instruct-abliterated-v2 - jeffmeloy/Qwen2.5-7B-olm-v1.0 - nvidia/AceMath-7B-Instruct - Krystalan/DRT-o1-7B library_name: transformers tags: - mergekit - merge --- # merge This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ## Merge Details ### Merge Method This model was merged using the [SCE](https://arxiv.org/abs/2408.07990) merge method using [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co./Qwen/Qwen2.5-7B-Instruct) as a base. ### Models Merged The following models were included in the merge: * [Aashraf995/Qwen-Evo-7B](https://huggingface.co./Aashraf995/Qwen-Evo-7B) * [jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0](https://huggingface.co./jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0) * [Goekdeniz-Guelmez/Josiefied-Qwen2.5-7B-Instruct-abliterated-v2](https://huggingface.co./Goekdeniz-Guelmez/Josiefied-Qwen2.5-7B-Instruct-abliterated-v2) * [jeffmeloy/Qwen2.5-7B-olm-v1.0](https://huggingface.co./jeffmeloy/Qwen2.5-7B-olm-v1.0) * [nvidia/AceMath-7B-Instruct](https://huggingface.co./nvidia/AceMath-7B-Instruct) * [Krystalan/DRT-o1-7B](https://huggingface.co./Krystalan/DRT-o1-7B) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: Goekdeniz-Guelmez/Josiefied-Qwen2.5-7B-Instruct-abliterated-v2 # Best for Benchmark 1 parameters: density: 0.2 weight: 0.167 - model: Aashraf995/Qwen-Evo-7B # Best for Benchmark 2 parameters: density: 0.2 weight: 0.167 - model: nvidia/AceMath-7B-Instruct # Best for Benchmark 3 parameters: density: 0.2 weight: 0.167 - model: Krystalan/DRT-o1-7B # Best for Benchmark 4 parameters: density: 0.2 weight: 0.167 - model: jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0 # Best for Benchmark 5 parameters: density: 0.2 weight: 0.167 - model: jeffmeloy/Qwen2.5-7B-olm-v1.0 # Best for Benchmark 6 parameters: density: 0.2 weight: 0.167 merge_method: sce base_model: Qwen/Qwen2.5-7B-Instruct # Replace if using a different base model parameters: normalize: false int8_mask: true select_topk: 0.5 # Retains top 10% highest variance elements (adjust for better results) dtype: bfloat16 allow_crimes: true ```