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Model: steve-nguyen/aai-accountant-tt133-v1.1
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- vi
+- en
+license: apache-2.0
+base_model: Qwen/Qwen3-4B-Instruct-2507
+tags:
+- qwen3
+- accounting
+- vietnamese
+- kế-toán
+- thông-tư-133
+- fine-tuned
+- cot
+- chain-of-thought
+datasets:
+- custom-tt133
+pipeline_tag: text-generation
+---
+
+# AAI Accountant — TT133 v1.1
+
+**AI tư vấn kế toán chuyên biệt cho Thông tư 133/2016/TT-BTC** (Chế độ kế toán doanh nghiệp nhỏ và vừa Việt Nam)
+
+**Phiên bản 1.1** (Cải tiến: tăng độ chính xác câu trả lời, giảm halluciation)
+
+## Thông tin mô hình
+
+| Thuộc tính | Giá trị |
+|---|---|
+| Base model | `Qwen/Qwen3-4B-Instruct-2507` |
+| Fine-tune method | LoRA FP16 (rank=32, RSLoRA) |  *(✅ FIX B-08)*
+| Dataset | 1484 samples từ TT133 + Phụ lục biểu mẫu + Nghiệp vụ|
+| Language | Tiếng Việt (kế toán) |
+| Context length | 4096 tokens |
+| Format | ChatML + `<think>...</think>` CoT |
+
+## Khả năng
+
+- ✅ **Hướng dẫn định khoản kế toán** theo TT133 (Nợ/Có, TK XXX)
+- ✅ **Giải thích điều khoản** — trả lời câu hỏi về 91 Điều của TT133
+- ✅ **Biểu mẫu BCTC** — hướng dẫn điền B01-DNN, B02-DNN, B09-DNN...
+- ✅ **Danh mục tài khoản** — tra cứu mã TK, phân loại, bút toán điển hình
+- ✅ **Chain-of-Thought** — suy luận từng bước rõ ràng trước khi trả lời
+
+## Dataset breakdown
+
+| Loại nội dung | Samples | % |
+|---|---|---|
+| Văn bản (Điều khoản chung) | 267 | 18% |
+| Nguyên tắc kế toán | 249 | 17% |
+| Biểu mẫu (Phụ lục) | 358 | 24% |
+| Ví dụ | 72 | 5% |
+| Định khoản Nợ/Có | 447 | 30% |
+| Phụ lục chung | 91 | 6% |
+
+## Cách dùng
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = 'steve-nguyen/aai-accountant-tt133-v1.1'
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id, torch_dtype=torch.float16, device_map='auto'
+)
+# System prompt
+SYSTEM_STRICT = '''Bạn là AI kế toán chuyên biệt theo Thông tư 133/2016/TT-BTC.
+QUY TẮC BẮT BUỘC:
+1. Chỉ nhắc các TK có thật trong TT133 (TK 111–911, theo danh mục TT133)
+2. Khi hỏi về B01-DNN/B02-DNN, trả lời đúng mapping: Mã số → TK nguồn
+3. Nếu không chắc chắn 100%, nói rõ: "Cần kiểm tra lại với văn bản TT133"
+4. Không liệt kê TK theo pattern số tăng dần nếu không chắc
+Nguyên tắc: Chính xác > Đầy đủ. Thà ít mà đúng hơn nhiều mà sai.'''
+
+def ask(question, max_new_tokens=1024):
+    messages = [
+        {'role': 'system', 'content': SYSTEM_STRICT},
+        {'role': 'user',   'content': question},
+    ]
+    chat_text = tokenizer.apply_chat_template(
+        messages, tokenize=False, add_generation_prompt=True,
+        enable_thinking=True,
+    )
+    encoded = tokenizer(chat_text, return_tensors='pt').to('cuda')
+    prompt_len = encoded['input_ids'].shape[1]
+
+    with torch.no_grad():
+        outputs = model.generate(
+            **encoded,
+            max_new_tokens       = max_new_tokens,
+            do_sample            = True,
+            temperature          = 0.1,
+            top_p                = 0.9,
+            repetition_penalty   = 1.05,
+            eos_token_id         = tokenizer.eos_token_id,
+            pad_token_id         = tokenizer.eos_token_id,
+        )
+
+    text = tokenizer.decode(outputs[0][prompt_len:], skip_special_tokens=True)
+
+    import re
+    text = re.sub(r'<think>.*?</think>', '', text, flags=re.DOTALL).strip()
+    return text
+
+    try:
+        chat_text = tokenizer.apply_chat_template(
+            messages,
+            tokenize=False,
+            add_generation_prompt=True,
+            enable_thinking=False,
+        )
+    except TypeError:
+        chat_text = tokenizer.apply_chat_template(
+            messages, tokenize=False, add_generation_prompt=True,
+        )
+
+    encoded = tokenizer(
+        chat_text, return_tensors='pt', return_attention_mask=True,
+    ).to('cuda')
+
+    input_ids      = encoded['input_ids']
+    attention_mask = encoded['attention_mask']
+    prompt_len     = input_ids.shape[1]
+
+    with torch.no_grad():
+        outputs = model.generate(
+            input_ids            = input_ids,
+            attention_mask       = attention_mask,
+            max_new_tokens       = max_new_tokens,
+            do_sample            = False,
+            temperature          = 1.0,
+            repetition_penalty   = 1.1,
+            no_repeat_ngram_size = 5,
+            eos_token_id         = tokenizer.eos_token_id,
+            pad_token_id         = tokenizer.eos_token_id,
+            use_cache            = True,
+        )
+
+    generated = outputs[0][prompt_len:]
+    text = tokenizer.decode(generated, skip_special_tokens=True)
+
+    import re
+    text = re.sub(r'<think>.*?</think>', '', text, flags=re.DOTALL).strip()
+    return text
+
+print('✅ ask() sẵn sàng — inference mode ON')
+print('   enable_thinking=False | do_sample=False (greedy decoding)')
+
+#Đặt câu hỏi
+q1 = 'Công ty ABC mua hàng hóa giá 100 triệu đồng, chưa trả tiền người bán. Hãy định khoản nghiệp vụ này theo TT133.'
+print('='*60)
+print('❓', q1)
+print('='*60)
+print(ask(q1))
+```
+
+## Lưu ý
+
+- Mô hình được tối ưu cho **Thông tư 133** (Doanh nghiệp Vừa và Nhỏ).
+- Một số trường hợp Mô hình trả lời không đúng yêu cầu, chỉ cần điều chình System prompt (SYSTEM_STRICT).
+- Luôn kiểm tra lại bút toán với kế toán viên — AI có thể mắc lỗi trong các trường hợp phức tạp.
+- Không áp dụng cho mục đích pháp lý mà không có xác nhận chuyên môn.
+
+## License
+
+Apache 2.0 — kế thừa từ Qwen3-4B-Instruct.
+
+## Góp ý
+
+Mọi ý kiến đóng góp xin gởi vào email: anh.nd@outlook.com

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# 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 %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- 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>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- 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

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+{
+    "architectures": [
+        "Qwen3ForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": null,
+    "torch_dtype": "float16",
+    "eos_token_id": 151645,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 2560,
+    "initializer_range": 0.02,
+    "intermediate_size": 9728,
+    "layer_types": [
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "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,
+    "unsloth_fixed": true,
+    "unsloth_version": "2026.4.7",
+    "use_cache": false,
+    "use_sliding_window": false,
+    "vocab_size": 151936
+}

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tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d7430e9138b76e93fb6f93462394d236b411111aef53cb421ba97d2691040cca
+size 11423114

tokenizer_config.json

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+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "is_local": false,
+  "model_max_length": 262144,
+  "pad_token": "<|PAD_TOKEN|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
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+  "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' }}\n{%- endif %}"
+}