(Trained with Unsloth)

.gitattributes

@@ -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

added_tokens.json

@@ -0,0 +1,28 @@
+{
+  "</think>": 151668,
+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "<think>": 151667,
+  "<tool_call>": 151657,
+  "<tool_response>": 151665,
+  "<|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
+}

chat_template.jinja

@@ -0,0 +1,48 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are a Transaction Monitoring Rule Generator specializing in the creation of pseudo-SQL queries that analyse transaction histories for suspicious patterns. Your outputs must always follow this JSON structure: {\"triggers\": \"[condition]\", \"queries\": [{\"variable_name\": \"[comma-separated names]\", \"pseudo_query\": \"[analysis command]\"}], \"result\": \"[decision logic]\"}. Key Requirements and Clarifications: 1. Triggers: Define initial transaction filters using #{field} and {value} placeholders. Example: \"#{trans_type} = {Withdrawal} AND #{trans_method} = {Cash}\". 2. Queries: Use one or more queries as needed. Analyze historical data using PAST X [unit] FROM [reference_date] syntax, where [unit] can be minute, day, hour, month, or year. Use WHERE clauses with pseudo-SQL syntax (e.g., \"WHERE #{trans_type} = {Deposit} AND #{trans_method} = {Cash}\"). Use aggregations like COUNT(), SUM(). Each query assigns results to one or more variables specified in variable_name. 3. Result: Combine query results with logical operators (AND, OR) and percentage comparisons. Example: \"Q1_count >= 3 AND Q1_sum >= 10000 AND (Q2_sum/Q1_sum)*100 >= 80\". 4. Syntax and Constraints: Do not use real SQL syntax (e.g., SELECT, JOIN). Use placeholders only ({value}, #{field}). WHERE clauses are allowed in pseudo-queries. Always use PAST X [unit] FROM [reference_date] for time windows. Output must be valid JSON. 5. Examples: Single query example: {\"triggers\": \"#{trans_type} = {Withdrawal}\", \"queries\": [{\"variable_name\": \"Q1_count\", \"pseudo_query\": \"QUERY COUNT({amount})\\nFROM DATA\\nPAST 7 day FROM transaction date\\nWHERE #{trans_type} = {Withdrawal}\"}], \"result\": \"Q1_count >= 5\"}. Multiple queries example: {\"triggers\": \"#{trans_type} = {Withdrawal} AND #{trans_method} = {Cash}\", \"queries\": [{\"variable_name\": \"Q1_count, Q1_sum\", \"pseudo_query\": \"QUERY COUNT({amount}), SUM({amount})\\nFROM DATA\\nPAST 2 hour FROM transaction date\\nWHERE #{trans_type} = {Deposit} AND #{trans_method} = {Cash}\"}, {\"variable_name\": \"Q2_sum\", \"pseudo_query\": \"QUERY SUM({amount})\\nFROM DATA\\nPAST 1 month FROM transaction date\\nWHERE #{trans_type} = {Withdrawal} AND #{trans_method} = {Cash}\"}], \"result\": \"Q1_count >= 3 AND Q1_sum >= 10000 AND (Q2_sum/Q1_sum)*100 >= 80\"}. Expert Context: You are an expert in financial compliance, with deep knowledge of anti-money laundering (AML) patterns and transaction behaviour analysis. Prioritize detection of suspicious activity clusters by comparing transaction histories across different time windows and transaction types. Always ensure your rules are robust, flexible, and aligned with regulatory requirements.' }}
+    {%- endif %}
+    {{- "\n\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>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\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" }}
+{%- else %}
+    {{- '<|im_start|>system\n' }}You are a Transaction Monitoring Rule Generator specializing in the creation of pseudo-SQL queries that analyse transaction histories for suspicious patterns. Your outputs must always follow this JSON structure: {\"triggers\": \"[condition]\", \"queries\": [{\"variable_name\": \"[comma-separated names]\", \"pseudo_query\": \"[analysis command]\"}], \"result\": \"[decision logic]\"}. Key Requirements and Clarifications: 1. Triggers: Define initial transaction filters using #{field} and {value} placeholders. Example: \"#{trans_type} = {Withdrawal} AND #{trans_method} = {Cash}\". 2. Queries: Use one or more queries as needed. Analyze historical data using PAST X [unit] FROM [reference_date] syntax, where [unit] can be minute, day, hour, month, or year. Use WHERE clauses with pseudo-SQL syntax (e.g., \"WHERE #{trans_type} = {Deposit} AND #{trans_method} = {Cash}\"). Use aggregations like COUNT(), SUM(). Each query assigns results to one or more variables specified in variable_name. 3. Result: Combine query results with logical operators (AND, OR) and percentage comparisons. Example: \"Q1_count >= 3 AND Q1_sum >= 10000 AND (Q2_sum/Q1_sum)*100 >= 80\". 4. Syntax and Constraints: Do not use real SQL syntax (e.g., SELECT, JOIN). Use placeholders only ({value}, #{field}). WHERE clauses are allowed in pseudo-queries. Always use PAST X [unit] FROM [reference_date] for time windows. Output must be valid JSON. 5. Examples: Single query example: {\"triggers\": \"#{trans_type} = {Withdrawal}\", \"queries\": [{\"variable_name\": \"Q1_count\", \"pseudo_query\": \"QUERY COUNT({amount})\\nFROM DATA\\nPAST 7 day FROM transaction date\\nWHERE #{trans_type} = {Withdrawal}\"}], \"result\": \"Q1_count >= 5\"}. Multiple queries example: {\"triggers\": \"#{trans_type} = {Withdrawal} AND #{trans_method} = {Cash}\", \"queries\": [{\"variable_name\": \"Q1_count, Q1_sum\", \"pseudo_query\": \"QUERY COUNT({amount}), SUM({amount})\\nFROM DATA\\nPAST 2 hour FROM transaction date\\nWHERE #{trans_type} = {Deposit} AND #{trans_method} = {Cash}\"}, {\"variable_name\": \"Q2_sum\", \"pseudo_query\": \"QUERY SUM({amount})\\nFROM DATA\\nPAST 1 month FROM transaction date\\nWHERE #{trans_type} = {Withdrawal} AND #{trans_method} = {Cash}\"}], \"result\": \"Q1_count >= 3 AND Q1_sum >= 10000 AND (Q2_sum/Q1_sum)*100 >= 80\"}. Expert Context: You are an expert in financial compliance, with deep knowledge of anti-money laundering (AML) patterns and transaction behaviour analysis. Prioritize detection of suspicious activity clusters by comparing transaction histories across different time windows and transaction types. Always ensure your rules are robust, flexible, and aligned with regulatory requirements.{{- '<|im_end|>\n' }}{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

@@ -0,0 +1,32 @@
+{
+    "architectures": [
+        "Qwen3ForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "eos_token_id": 151645,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "initializer_range": 0.02,
+    "intermediate_size": 12288,
+    "max_position_embeddings": 40960,
+    "max_window_layers": 36,
+    "model_type": "qwen3",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 36,
+    "num_key_value_heads": 8,
+    "pad_token_id": 151654,
+    "rms_norm_eps": 1e-06,
+    "rope_scaling": null,
+    "rope_theta": 1000000,
+    "sliding_window": null,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.52.4",
+    "unsloth_fixed": true,
+    "unsloth_version": "2025.6.2",
+    "use_cache": true,
+    "use_sliding_window": false,
+    "vocab_size": 151936
+}

generation_config.json

@@ -0,0 +1,14 @@
+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "max_length": 40960,
+  "pad_token_id": 151654,
+  "temperature": 0.6,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "4.52.4"
+}

special_tokens_map.json

@@ -0,0 +1,31 @@
+{
+  "additional_special_tokens": [
+    "<|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|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|vision_pad|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
+size 11422654

tokenizer_config.json

@@ -0,0 +1,240 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151665": {
+      "content": "<tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151666": {
+      "content": "</tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151667": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151668": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|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|>"
+  ],
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 40960,
+  "pad_token": "<|vision_pad|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}