Create README.md
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README.md
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---
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base_model:
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- meta-llama/Meta-Llama-3-70B-Instruct
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license: llama3
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- merge
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- frankenmerge
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- 96b
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---
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# BigWeave v33 105b
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<img src="https://cdn-uploads.huggingface.co/production/uploads/65a6db055c58475cf9e6def1/4CbbAN-X7ZWj702JrcCGH.png" width=600>
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The BigWeave models aim to experimentally identify merge settings for increasing model performance. The version number merely tracks various attempts and is not a quality indicator. Only results demonstrating good performance are retained and shared.
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# Prompting Format
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llamav3
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# Merge process
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This is a self-merge of meta-llama/Meta-Llama-3-70B-Instruct. Middle layers are duplicated and various matrices are scaled according to the template by jukofyork as shown here: https://github.com/arcee-ai/mergekit/issues/198#issuecomment-2079950009
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Merge configuration:
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```
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const_tag: &MODEL meta-llama/Meta-Llama-3-70B-Instruct
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const_tag: &RESIDUAL_SCALE_FACTOR 0.5
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const_tag: &QK_ATTENUATION_FACTOR 0.7071067812
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const_tag: &OUT_FACTOR 0.9
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scale-filter-env: &scale_filter_env
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parameters:
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scale:
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- filter: o_proj
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value: *RESIDUAL_SCALE_FACTOR
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- filter: down_proj
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value: *RESIDUAL_SCALE_FACTOR
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- filter: q_proj
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value: *QK_ATTENUATION_FACTOR
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- filter: k_proj
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value: *QK_ATTENUATION_FACTOR
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- filter: v_proj
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value: *OUT_FACTOR
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- filter: up_proj
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value: *OUT_FACTOR
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- value: 1.0
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slices:
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- sources:
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- model: *MODEL
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layer_range: [0, 19]
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- sources:
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- model: *MODEL
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layer_range: [19, 20]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL
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layer_range: [10, 29]
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- sources:
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- model: *MODEL
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layer_range: [29, 30]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL
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layer_range: [20, 39]
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- sources:
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- model: *MODEL
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layer_range: [39, 40]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL
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layer_range: [30, 49]
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- sources:
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- model: *MODEL
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layer_range: [49, 50]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL
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layer_range: [40, 80]
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merge_method: passthrough
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dtype: float16
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```
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