--- base_model: - allura-org/Qwen2.5-32b-RP-Ink - deepseek-ai/DeepSeek-R1-Distill-Qwen-32B - Aryanne/QwentileSwap - Daemontatox/Cogito-Ultima library_name: transformers tags: - mergekit - merge --- # Qwetiapin > There's no 'I' in 'brain damage' ![](https://files.catbox.moe/9k5p1v.png) ### Overview An attempt to make QwentileSwap write even better by merging it with RP-Ink. And DeepSeek, because why not. However, I screwed up the first merge step by accidentally setting an extremely high epsilon value. Step2 wasn't planned, but due to a wonky tensor size mismatch error, I couldn't merge Step1 into QwentileSwap using sce, so I just threw in some random model. And that did, in fact, solve the issue. The result? Well, it's usable, I guess. The slop is reduced, more details are brought up, but said details sometimes get messed up. It's fixed by a few swipes and there's a chance that it's caused by my sampler settings, but uhh I'll just leave them as they are. Prompt format: ChatML Settings: [This kinda works but I'm weird](https://files.catbox.moe/hmw87j.json) ### Quants [Static](https://huggingface.co/mradermacher/Q2.5-Qwetiapin-32B-GGUF) | [Imatrix](https://huggingface.co/mradermacher/Q2.5-Qwetiapin-32B-i1-GGUF) ## Merge Details ### Merging Steps ### Step1 ```yaml dtype: bfloat16 tokenizer_source: base merge_method: della_linear parameters: density: 0.5 epsilon: 0.4 #was supposed to be 0.04 lambda: 1.1 base_model: allura-org/Qwen2.5-32b-RP-Ink models: - model: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B parameters: weight: - filter: v_proj value: [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0] - filter: o_proj value: [1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1] - filter: up_proj value: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] - filter: gate_proj value: [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0] - filter: down_proj value: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] - value: 0 - model: allura-org/Qwen2.5-32b-RP-Ink parameters: weight: - filter: v_proj value: [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1] - filter: o_proj value: [0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0] - filter: up_proj value: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] - filter: gate_proj value: [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1] - filter: down_proj value: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] - value: 1 ``` ### Step2 ```yaml models: - model: Aryanne/QwentileSwap parameters: weight: [1.0, 0.9, 0.8, 0.9, 1.0] - model: Daemontatox/Cogito-Ultima parameters: weight: [0, 0.1, 0.2, 0.1, 0] merge_method: nuslerp parameters: nuslerp_row_wise: true dtype: bfloat16 tokenizer_source: base ``` ### Step3 ```yaml models: - model: Step2 - model: Step1 merge_method: sce base_model: Step2 parameters: select_topk: - value: [0.3, 0.35, 0.4, 0.35, 0.2] dtype: bfloat16 ```