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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,122 @@
+---
+base_model:
+- qingy2024/Fusion4-14B-Instruct
+- sometimesanotion/Lamarck-14B-v0.6
+- allknowingroger/QwenSlerp6-14B
+- CultriX/SeQwence-14B-EvolMerge
+- CultriX/Qwen2.5-14B-Wernickev3
+- hotmailuser/QwenSlerp2-14B
+- CultriX/Qwen2.5-14B-Emerged
+- djuna/Q2.5-Veltha-14B-0.5
+library_name: transformers
+tags:
+- mergekit
+- merge
+
+---
+# merge
+
+This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+
+## Merge Details
+### Merge Method
+
+This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [CultriX/Qwen2.5-14B-Wernickev3](https://huggingface.co/CultriX/Qwen2.5-14B-Wernickev3) as a base.
+
+### Models Merged
+
+The following models were included in the merge:
+* [qingy2024/Fusion4-14B-Instruct](https://huggingface.co/qingy2024/Fusion4-14B-Instruct)
+* [sometimesanotion/Lamarck-14B-v0.6](https://huggingface.co/sometimesanotion/Lamarck-14B-v0.6)
+* [allknowingroger/QwenSlerp6-14B](https://huggingface.co/allknowingroger/QwenSlerp6-14B)
+* [CultriX/SeQwence-14B-EvolMerge](https://huggingface.co/CultriX/SeQwence-14B-EvolMerge)
+* [hotmailuser/QwenSlerp2-14B](https://huggingface.co/hotmailuser/QwenSlerp2-14B)
+* [CultriX/Qwen2.5-14B-Emerged](https://huggingface.co/CultriX/Qwen2.5-14B-Emerged)
+* [djuna/Q2.5-Veltha-14B-0.5](https://huggingface.co/djuna/Q2.5-Veltha-14B-0.5)
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+merge_method: dare_ties # Changed to dare_ties
+base_model: CultriX/Qwen2.5-14B-Wernickev3
+dtype: bfloat16 # Use float32 for maximum precision.
+out_dtype: bfloat16  # Output model also uses bfloat16 for consistency and reduced memory usage.
+
+parameters:
+  t: 0.5  # Balances interpolation between models; 0.5 gives equal weight to all contributors.
+  normalize: true  # Ensures parameters are normalized to maintain stability during merging.
+  rescale: true  # Aligns parameter scales across models for better integration.
+  int8_mask: false  # Disable int8 masking to preserve full precision during merging.
+  epsilon: 0.008  # Ultra-fine parameter scaling for precise adjustments between models.
+  lambda: 1.8  # Emphasizes high-impact parameters, giving more weight to significant contributors.
+
+adaptive_merge_parameters:
+  task_weights:  # Assign weights to tasks based on their priority and impact on benchmarks.
+    tinyArc: 1.6  # Logical reasoning benchmark; slightly lower priority.
+    tinyHellaswag: 1.5  # Contextual reasoning benchmark with moderate priority.
+    tinyMMLU: 1.8  # Multi-domain knowledge benchmark; important for multitask performance.
+    tinyTruthfulQA: 1.9  # Focuses on factual reasoning and QA; high priority.
+    tinyTruthfulQA_mc1: 1.75  # Multiple-choice factual reasoning; closely related to TruthfulQA.
+    tinyWinogrande: 1.75  # Core reasoning benchmark; slightly lower than BBH.
+    IFEval: 2.30  # Instruction-following tasks; given a high priority for practical applications.
+    BBH: 2.05  # Complex reasoning benchmark; critical for logical tasks.
+    MATH: 2.70  # Highest priority to emphasize mathematical reasoning excellence.
+    GPQA: 2.20  # Graduate-level QA tasks; balanced priority for high-level reasoning.
+    MUSR: 2.15  # Multi-step reasoning; slightly increased to strengthen reasoning performance.
+    MMLU-PRO: 2.00  # Domain multitask benchmark; maintained for general multitask capability.
+  smoothing_factor: 0.03  # Low smoothing for precise task-specific blending without over-generalizing.
+
+gradient_clipping:  # Control gradient clipping for each model to stabilize training.
+  CultriX/Qwen2.5-14B-Wernickev3: 0.89  # Higher value ensures stability for the base model.
+  djuna/Q2.5-Veltha-14B-0.5: 0.92  # Stable setting to enhance reasoning contributions.
+  CultriX/SeQwence-14B-EvolMerge: 0.87  # Moderate value for generalist multitask support.
+  qingy2024/Fusion4-14B-Instruct: 0.93  # High stability to emphasize mathematical tasks.
+  CultriX/Qwen2.5-14B-Emerged: 0.88  # Stable setting to maintain multitask performance.
+  sometimesanotion/Lamarck-14B-v0.6: 0.89  # Stable contribution for multi-step reasoning.
+  allknowingroger/QwenSlerp6-14B: 0.90  # Adjusted for stable integration of the replacement model.
+  hotmailuser/QwenSlerp2-14B: 0.91  # Increased slightly for stable integration of reasoning contributions.
+
+models:  # Define models to include in the merge, along with their weights and densities.
+  - model: CultriX/Qwen2.5-14B-Wernickev3
+    parameters:
+      weight: 0.33  # Increased to absorb some of the weight from the removed model.
+      density: 0.78  # Maintained optimal density for robust generalist performance.
+
+  - model: djuna/Q2.5-Veltha-14B-0.5
+    parameters:
+      weight: 0.28  # Increased slightly to enhance reasoning benchmarks like MUSR.
+      density: 0.77  # Maintained for strong nuanced reasoning.
+
+  - model: allknowingroger/QwenSlerp6-14B  # Replacement for Qwenfinity-2.5-14B.
+    parameters:
+      weight: 0.15  # Matches the weight of the replaced model to preserve balance.
+      density: 0.70  # Increased slightly for stronger parameter integration.
+
+  - model: CultriX/SeQwence-14B-EvolMerge
+    parameters:
+      weight: 0.12  # Moderate weight for general multitask support.
+      density: 0.62  # Maintained for stable contribution.
+
+  - model: qingy2024/Fusion4-14B-Instruct
+    parameters:
+      weight: 0.09  # Moderate weight; focuses on mathematical reasoning tasks.
+      density: 0.75  # Maintained density for stable integration.
+
+  - model: CultriX/Qwen2.5-14B-Emerged
+    parameters:
+      weight: 0.08  # Balanced weight for multitask contributions.
+      density: 0.69  # Maintained density for stable integration.
+
+  - model: sometimesanotion/Lamarck-14B-v0.6
+    parameters:
+      weight: 0.06  # Lower weight to allow more impactful models to dominate.
+      density: 0.62  # Maintained for stable multi-step reasoning contribution.
+
+  - model: hotmailuser/QwenSlerp2-14B
+    parameters:
+      weight: 0.11  # Increased slightly to balance contributions.
+      density: 0.66  # Maintained for stable parameter integration.
+
+```

added_tokens.json

@@ -0,0 +1,24 @@
+{
+  "</tool_call>": 151658,
+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

config.json

@@ -0,0 +1,29 @@
+{
+  "_name_or_path": "CultriX/Qwen2.5-14B-Wernickev3",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 13824,
+  "max_position_embeddings": 131072,
+  "max_window_layers": 48,
+  "model_type": "qwen2",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 48,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.46.2",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151665
+}

mergekit_config.yml

@@ -0,0 +1,79 @@
+merge_method: dare_ties # Changed to dare_ties
+base_model: CultriX/Qwen2.5-14B-Wernickev3
+dtype: bfloat16 # Use float32 for maximum precision.
+out_dtype: bfloat16  # Output model also uses bfloat16 for consistency and reduced memory usage.
+
+parameters:
+  t: 0.5  # Balances interpolation between models; 0.5 gives equal weight to all contributors.
+  normalize: true  # Ensures parameters are normalized to maintain stability during merging.
+  rescale: true  # Aligns parameter scales across models for better integration.
+  int8_mask: false  # Disable int8 masking to preserve full precision during merging.
+  epsilon: 0.008  # Ultra-fine parameter scaling for precise adjustments between models.
+  lambda: 1.8  # Emphasizes high-impact parameters, giving more weight to significant contributors.
+
+adaptive_merge_parameters:
+  task_weights:  # Assign weights to tasks based on their priority and impact on benchmarks.
+    tinyArc: 1.6  # Logical reasoning benchmark; slightly lower priority.
+    tinyHellaswag: 1.5  # Contextual reasoning benchmark with moderate priority.
+    tinyMMLU: 1.8  # Multi-domain knowledge benchmark; important for multitask performance.
+    tinyTruthfulQA: 1.9  # Focuses on factual reasoning and QA; high priority.
+    tinyTruthfulQA_mc1: 1.75  # Multiple-choice factual reasoning; closely related to TruthfulQA.
+    tinyWinogrande: 1.75  # Core reasoning benchmark; slightly lower than BBH.
+    IFEval: 2.30  # Instruction-following tasks; given a high priority for practical applications.
+    BBH: 2.05  # Complex reasoning benchmark; critical for logical tasks.
+    MATH: 2.70  # Highest priority to emphasize mathematical reasoning excellence.
+    GPQA: 2.20  # Graduate-level QA tasks; balanced priority for high-level reasoning.
+    MUSR: 2.15  # Multi-step reasoning; slightly increased to strengthen reasoning performance.
+    MMLU-PRO: 2.00  # Domain multitask benchmark; maintained for general multitask capability.
+  smoothing_factor: 0.03  # Low smoothing for precise task-specific blending without over-generalizing.
+
+gradient_clipping:  # Control gradient clipping for each model to stabilize training.
+  CultriX/Qwen2.5-14B-Wernickev3: 0.89  # Higher value ensures stability for the base model.
+  djuna/Q2.5-Veltha-14B-0.5: 0.92  # Stable setting to enhance reasoning contributions.
+  CultriX/SeQwence-14B-EvolMerge: 0.87  # Moderate value for generalist multitask support.
+  qingy2024/Fusion4-14B-Instruct: 0.93  # High stability to emphasize mathematical tasks.
+  CultriX/Qwen2.5-14B-Emerged: 0.88  # Stable setting to maintain multitask performance.
+  sometimesanotion/Lamarck-14B-v0.6: 0.89  # Stable contribution for multi-step reasoning.
+  allknowingroger/QwenSlerp6-14B: 0.90  # Adjusted for stable integration of the replacement model.
+  hotmailuser/QwenSlerp2-14B: 0.91  # Increased slightly for stable integration of reasoning contributions.
+
+models:  # Define models to include in the merge, along with their weights and densities.
+  - model: CultriX/Qwen2.5-14B-Wernickev3
+    parameters:
+      weight: 0.33  # Increased to absorb some of the weight from the removed model.
+      density: 0.78  # Maintained optimal density for robust generalist performance.
+
+  - model: djuna/Q2.5-Veltha-14B-0.5
+    parameters:
+      weight: 0.28  # Increased slightly to enhance reasoning benchmarks like MUSR.
+      density: 0.77  # Maintained for strong nuanced reasoning.
+
+  - model: allknowingroger/QwenSlerp6-14B  # Replacement for Qwenfinity-2.5-14B.
+    parameters:
+      weight: 0.15  # Matches the weight of the replaced model to preserve balance.
+      density: 0.70  # Increased slightly for stronger parameter integration.
+
+  - model: CultriX/SeQwence-14B-EvolMerge
+    parameters:
+      weight: 0.12  # Moderate weight for general multitask support.
+      density: 0.62  # Maintained for stable contribution.
+
+  - model: qingy2024/Fusion4-14B-Instruct
+    parameters:
+      weight: 0.09  # Moderate weight; focuses on mathematical reasoning tasks.
+      density: 0.75  # Maintained density for stable integration.
+
+  - model: CultriX/Qwen2.5-14B-Emerged
+    parameters:
+      weight: 0.08  # Balanced weight for multitask contributions.
+      density: 0.69  # Maintained density for stable integration.
+
+  - model: sometimesanotion/Lamarck-14B-v0.6
+    parameters:
+      weight: 0.06  # Lower weight to allow more impactful models to dominate.
+      density: 0.62  # Maintained for stable multi-step reasoning contribution.
+
+  - model: hotmailuser/QwenSlerp2-14B
+    parameters:
+      weight: 0.11  # Increased slightly to balance contributions.
+      density: 0.66  # Maintained for stable parameter integration.

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special_tokens_map.json

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+{
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+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
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+  "eos_token": {
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
+size 11421896

tokenizer_config.json

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+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
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+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}