Qwen2.5 Merged
Collection
Making Qwen2.5 greater with Merging
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6 items
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Updated
This is a merge of pre-trained language models created using mergekit.
Metric | Value |
---|---|
GSM8k (zero-shot) | 87.79 |
HellaSwag (zero-Shot) | 34.29 |
MBPP (zero-shot) | 60.41 |
This model was merged using the Linear DARE merge method using Qwen/Qwen2.5-7B as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
base_model: Qwen/Qwen2.5-7B
dtype: bfloat16
merge_method: dare_linear
parameters:
lambda: 0.690661354021995
normalize: 1.0
slices:
- sources:
- layer_range: [0, 28]
model: Qwen/Qwen2.5-7B
- layer_range: [0, 28]
model: Qwen/Qwen2.5-Math-7B
parameters:
density: 0.9593725853706829
weight: 0.11472446469404357
- layer_range: [0, 28]
model: Qwen/Qwen2.5-Coder-7B
parameters:
density: 0.768281938201547
weight: 0.11350094855547865
- layer_range: [0, 28]
model: Qwen/Qwen2.5-7B-Instruct
parameters:
density: 0.48528478746069637
weight: 0.6453505470133651