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Model: khazarai/Qwen3-4B-Qwen3.6-plus-Reasoning-Slerp
Source: Original Platform

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README.md

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+---
+base_model:
+- khazarai/Qwen3-4B-Kimi2.5-Reasoning-Distilled
+- khazarai/Qwen3-4B-Qwen3.6-plus-Reasoning-Distilled
+library_name: transformers
+tags:
+- mergekit
+- merge
+license: apache-2.0
+pipeline_tag: text-generation
+language:
+- en
+datasets:
+- khazarai/kimi-2.5-high-reasoning-250x
+- khazarai/qwen3.6-plus-high-reasoning-500x
+---
+
+# khazarai/Qwen3-4B-Qwen3.6-plus-Reasoning-Slerp
+
+
+![alt="General Benchmark Comparison Chart"](benchmark/Merged_Model.png)
+
+*Note: The sharp drop in "Creative Writing" is an expected and accepted trade-off to maximize extreme logical reasoning and coding precision.*
+
+This model is a highly experimental and optimized reasoning model created through a surgical SLERP merge of two powerful 4B reasoning models. The goal of this merge was to combine the deep analytical capabilities of Kimi with the mathematical and structural precision of Qwen, while mitigating the catastrophic forgetting commonly seen in SFT model merges.
+After multiple iterations and layer-by-layer tensor analysis, we achieved a **"1+1=3 Synergy Effect"** in Logical Inference and Planning, outperforming both base models and the official Qwen Thinking model.
+
+
+### The "Golden Path" (V5) Strategy
+Standard SLERP merges often destroy RAG capabilities and syntax adherence. To solve this, this model utilizes a custom merge configuration:
+
+1.  **RAG/Vocabulary Fix:** `embed_tokens` and `lm_head` are strictly pinned to `1.0` (Qwen). The model reads and speaks purely using Qwen's vocabulary, completely eliminating the RAG degradation problem.
+2.  **Gradient Attention:** The intermediate attention and MLP layers follow a smooth gradient `[0, 0.1, 0.2, 0.3, 0.5, 0.7, 0.8, 0.9, 1]` to prevent weight interference in deep reasoning steps.
+
+## Benchmark Performance (Multi-Domain Reasoning)
+
+
+| Model | Score |
+| :--- | :--- |
+| **khazarai/Qwen3-4B-Qwen3.6-plus-Reasoning-Slerp** | **77.18** |
+| khazarai/Qwen3-4B-Kimi2.5-Reasoning-Distilled | 76.09 |
+| khazarai/Qwen3-4B-Qwen3.6-plus-Reasoning-Distilled | 75.64 |
+| Qwen/Qwen3-4B-Thinking-2507 | 73.73 |
+
+- **Benchmark**: khazarai/Multi-Domain-Reasoning-Benchmark
+- **Total Questions**: 100
+
+
+## 💡 Intended Use Cases
+
+* **Ideal for:** Complex logical deductions, Python code debugging, mathematical problem-solving, and strict RAG (Retrieval-Augmented Generation) pipelines.
+* **Not recommended for:** Creative writing, poetry, or highly imaginative storytelling.
+
+
+### Models Merged
+
+The following models were included in the merge:
+* [khazarai/Qwen3-4B-Kimi2.5-Reasoning-Distilled](https://huggingface.co/khazarai/Qwen3-4B-Kimi2.5-Reasoning-Distilled)
+* [khazarai/Qwen3-4B-Qwen3.6-plus-Reasoning-Distilled](https://huggingface.co/khazarai/Qwen3-4B-Qwen3.6-plus-Reasoning-Distilled)
+
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+
+models:
+  - model: khazarai/Qwen3-4B-Kimi2.5-Reasoning-Distilled
+  - model: khazarai/Qwen3-4B-Qwen3.6-plus-Reasoning-Distilled
+merge_method: slerp
+base_model: khazarai/Qwen3-4B-Kimi2.5-Reasoning-Distilled
+parameters:
+  t:
+    - filter: embed_tokens
+      value: 1
+      
+    - filter: lm_head
+      value: 1
+
+    - value: 1
+    
+    - filter: self
+      value: [0, 0.1, 0.2, 0.3, 0.5, 0.7, 0.8, 0.9, 1]
+      
+dtype: bfloat16
+```

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config.json

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+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": null,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 2560,
+  "initializer_range": 0.02,
+  "intermediate_size": 9728,
+  "layer_types": [
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+    "full_attention",
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+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
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+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 262144,
+  "max_window_layers": 36,
+  "model_type": "qwen3",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 8,
+  "pad_token_id": 151669,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 5000000,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.0.0",
+  "unsloth_fixed": true,
+  "unsloth_version": "2026.3.7",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

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+
+models:
+  - model: khazarai/Qwen3-4B-Kimi2.5-Reasoning-Distilled
+  - model: khazarai/Qwen3-4B-Qwen3.6-plus-Reasoning-Distilled
+merge_method: slerp
+base_model: khazarai/Qwen3-4B-Kimi2.5-Reasoning-Distilled
+parameters:
+  t:
+    - filter: embed_tokens
+      value: 1
+      
+    - filter: lm_head
+      value: 1
+
+    - value: 1
+    
+    - filter: self
+      value: [0, 0.1, 0.2, 0.3, 0.5, 0.7, 0.8, 0.9, 1]
+      
+dtype: bfloat16

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+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d7430e9138b76e93fb6f93462394d236b411111aef53cb421ba97d2691040cca
+size 11423114

tokenizer_config.json

@@ -0,0 +1,16 @@
+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "is_local": false,
+  "model_max_length": 262144,
+  "pad_token": "<|PAD_TOKEN|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n        {%- set ns.multi_step_tool = false %}\n        {%- set ns.last_query_index = index %}\n    {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- else %}\n            {%- if '</think>' in content %}\n                {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n                {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n            {%- endif %}\n        {%- endif %}\n        {%- if loop.index0 > ns.last_query_index %}\n            {%- if loop.last or (not loop.last and reasoning_content) %}\n                {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n            {%- else %}\n                {{- '<|im_start|>' + message.role + '\\n' + content }}\n            {%- endif %}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n<think>\\n' }}\n{%- endif %}"
+}