Info
Trying to make something different, feel free to try like or dislike or leave a feedback, I'm not claiming anything about anything.
I made one quant here (https://huggingface.co/Aryanne/QwentileSwap/blob/main/q4ks_QwentileSwap.gguf)
Also thanks to mradermacher for the other quants: gguf and gguf_imatrix_quants.
merged
This is a merge of pre-trained language models created using my custom method in mergekit.
Merge Details
Merge Method
This model was merged using the task_swapping merge method using win10/EVA-QwQ-32B-Preview 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: win10/EVA-QwQ-32B-Preview
dtype: bfloat16
merge_method: task_swapping
slices:
- sources:
- layer_range: [0, 64]
model: maldv/Qwentile2.5-32B-Instruct
parameters:
diagonal_offset: 2.0 # ignored here
random_mask: 0.666
random_mask_seed: 888.0
weight: 0.5
- layer_range: [0, 64]
model: ArliAI/Qwen2.5-32B-ArliAI-RPMax-v1.3
parameters:
diagonal_offset: 5.0
weight: 0.75
- layer_range: [0, 64]
model: Sao10K/32B-Qwen2.5-Kunou-v1
parameters:
diagonal_offset: 2.0 # ignored here
random_mask: 0.333
random_mask_seed: 12347888.0
weight: 0.5
- layer_range: [0, 64]
model: win10/EVA-QwQ-32B-Preview
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