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--- |
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base_model: |
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- sometimesanotion/Lamarck-14B-v0.7-Fusion |
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- sometimesanotion/Lamarck-14B-v0.7 |
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library_name: transformers |
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tags: |
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- mergekit |
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- merge |
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--- |
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# merge |
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The merits of multi-stage arcee_fusion merges are clearly shown in [sometimesanotion/Lamarck-14B-v0.7-Fusion](https://huggingface.co./sometimesanotion/Lamarck-14B-v0.7-Fusion), which has a valuable uptick in GPQA over its predecessors. Will its gains be maintained with a modified version of the SLERP recipe from [suayptalha/Lamarckvergence-14B](https://huggingface.co./suayptalha/Lamarckvergence-14B)? Let's find out what these weights for self-attention and perceptrons can unlock in this merge. |
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## Merge Details |
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### Merge Method |
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This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method. |
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### Models Merged |
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The following models were included in the merge: |
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* [sometimesanotion/Lamarck-14B-v0.7-Fusion](https://huggingface.co./sometimesanotion/Lamarck-14B-v0.7-Fusion) |
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* [sometimesanotion/Lamarck-14B-v0.7](https://huggingface.co./sometimesanotion/Lamarck-14B-v0.7) |
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### Configuration |
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The following YAML configuration was used to produce this model: |
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```yaml |
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name: LamarckInfusion-14B-v1 |
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base_model: sometimesanotion/Lamarck-14B-v0.7 |
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merge_method: slerp |
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tokenizer_source: base |
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dtype: float32 |
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out_dtype: bfloat16 |
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parameters: |
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t: |
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- filter: self_attn |
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value: [0.2, 0.5, 0.4, 0.6, 0.8] |
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- filter: mlp |
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value: [0.8, 0.5, 0.6, 0.4, 0.2] |
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- value: [ 0.00, 0.00, 0.08, 0.16, 0.32, 0.48, 0.48, 0.48, 0.48, 0.48, 0.40, 0.32, 0.24 ] |
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slices: |
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- sources: |
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- model: sometimesanotion/Lamarck-14B-v0.7 |
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layer_range: [ 0, 48 ] |
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- model: sometimesanotion/Lamarck-14B-v0.7-Fusion |
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layer_range: [ 0, 48 ] |
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``` |
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