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README.md
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- merge
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---
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#
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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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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
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* genstruct
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* kg
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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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- merge
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---
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# fmx-3b Augmentive Instruct (preview)
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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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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
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* genstruct
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* kg
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