--- language: - en license: apache-2.0 library_name: transformers tags: - mergekit - merge base_model: Nohobby/Qwen2.5-32B-Peganum-v0.1 quantized_by: waldie --- *** ## Peganum Many thanks to the authors of the models used! [Qwen2.5](https://huggingface.co/Qwen/Qwen2.5-32B) | [Qwen2.5-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) | [Qwen-2.5-Instruct-abliterated](https://huggingface.co/zetasepic/Qwen2.5-32B-Instruct-abliterated-v2) | [RPMax-v1.3-32B](https://huggingface.co/ArliAI/Qwen2.5-32B-ArliAI-RPMax-v1.3) | [EVA-Instruct-32B-v2](https://huggingface.co/ParasiticRogue/EVA-Instruct-32B-v2)([EVA-Qwen2.5-32B-v0.2](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2)+ [Qwen2.5-Gutenberg-Doppel-32B](https://huggingface.co/nbeerbower/Qwen2.5-Gutenberg-Doppel-32B)) *** ### Overview Main uses: RP Prompt format: ChatML Just trying out merging Qwen, because why not. Slightly fewer refusals than other Qwen tunes, while performance seems unaffected by abliteration. I've hardly used Q2.5 models before, so I can't really compare them beyond that. *** ### Quants GGUF: [Q5_K_S](https://huggingface.co/Nohobby/Qwen2.5-32B-Peganum-v0.1-Q5_K_S/resolve/main/Qwen2.5-32B-Peganum-v0.1-Q5_K_S.gguf?download=true) *** ### Settings Samplers: https://huggingface.co/Nohobby/Qwen2.5-32B-Peganum-v0.1/resolve/main/Peganum.json You can also use the SillyTavern presets listed on the [EVA-v0.2 model card](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2) *** ## Merge Details ### Merging steps ## Step1 (Config taken from [here](https://huggingface.co/grimjim/Llama-3-Instruct-abliteration-OVA-8B)) ```yaml base_model: zetasepic/Qwen2.5-32B-Instruct-abliterated-v2 dtype: bfloat16 merge_method: task_arithmetic parameters: normalize: false slices: - sources: - layer_range: [0, 64] model: zetasepic/Qwen2.5-32B-Instruct-abliterated-v2 - layer_range: [0, 64] model: unsloth/Qwen2.5-32B-Instruct parameters: weight: -1.0 ``` ## Step2 (Config taken from [here](https://huggingface.co/Pyroserenus/Orthrus-12b-v0.8)) ```yaml models: - model: unsloth/Qwen2.5-32B - model: Step1 parameters: weight: [0.50, 0.20] density: [0.75, 0.55] - model: ArliAI/Qwen2.5-32B-ArliAI-RPMax-v1.3 parameters: weight: [0.50, 0.80] density: [0.75, 0.85] merge_method: ties base_model: unsloth/Qwen2.5-32B parameters: int8_mask: true rescale: true normalize: false dtype: bfloat16 ``` ## Peganum (Config taken from [here](https://huggingface.co/sophosympatheia/Evathene-v1.0)) ```yaml models: - model: Step2 parameters: weight: 1 density: 1 - model: ParasiticRogue/EVA-Instruct-32B-v2 parameters: weight: [0.0, 0.2, 0.66, 0.8, 1.0, 0.8, 0.66, 0.2, 0.0] density: 0.5 merge_method: ties base_model: unsloth/Qwen2.5-32B parameters: normalize: true int8_mask: true dtype: bfloat16 ```