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--- |
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base_model: |
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- unsloth/Qwen2.5-3B-Instruct |
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- unsloth/Qwen2.5-3B |
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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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# merged_output_ties_1_4 |
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). |
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## Merge Details |
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### Merge Method |
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This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [unsloth/Qwen2.5-3B](https://huggingface.co/unsloth/Qwen2.5-3B) as a base. |
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### Models Merged |
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The following models were included in the merge: |
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* [unsloth/Qwen2.5-3B-Instruct](https://huggingface.co/unsloth/Qwen2.5-3B-Instruct) |
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* triples/merged_model |
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* genstruct/merged_model |
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* kg/merged_model |
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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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models: |
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# Base instructed model |
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- model: unsloth/Qwen2.5-3B-Instruct |
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parameters: |
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weight: 1 |
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density: 1 |
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# Merged LoRA models |
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- model: genstruct/merged_model |
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parameters: |
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weight: 1.0 |
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density: 1.0 |
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# - model: summary/merged_model |
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# parameters: |
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# weight: 1.0 |
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# density: 1.0 |
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- model: kg/merged_model |
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parameters: |
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weight: 1.0 |
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density: 1.0 |
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#### THIS BREAKS KG!!! |
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# - model: pII/merged_model |
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# parameters: |
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# weight: 1.0 |
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# density: 1.0 |
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# #### Breaks KG! |
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# - model: preference/merged_model |
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# parameters: |
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# weight: 1.0 |
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# density: 1.0 |
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- model: triples/merged_model |
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parameters: |
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weight: 1.0 |
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density: 1.0 |
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# - model: suitable/merged_model |
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# parameters: |
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# weight: 1.0 |
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# density: 1.0 |
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# - model: feedback/merged_model |
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# parameters: |
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# weight: 1.0 |
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# density: 1.0 |
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# Merge configuration |
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merge_method: ties |
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base_model: unsloth/Qwen2.5-3B |
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parameters: |
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normalize: true |
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int8_mask: true |
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dtype: bfloat16 |
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# # Tokenizer configuration |
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# tokenizer_source: Qwen/Qwen1.5-14B-Chat |
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# tokenizer_parameters: |
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# trust_remote_code: true |
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# # Output configuration |
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# output: |
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# precision: bfloat16 |
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# model_format: safetensors |
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# max_shard_size: "4GB" |
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# # Training configuration (for potential fine-tuning) |
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# training: |
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# learning_rate: 2e-5 |
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# warmup_steps: 100 |
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# gradient_checkpointing: true |
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# gradient_accumulation_steps: 4 |
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# # Hardware optimization |
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# hardware: |
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# mixed_precision: true |
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# cuda_memory_fraction: 0.95 |
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# optimize_model_memory: true |
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``` |
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