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Model: AudCor/cpa-qwen3-8b-v0
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---
license: apache-2.0
tags:
- text-generation
- finance
- economics
- cpa
- audcor
datasets:
- Josephgflowers/Finance-Instruct-500k
language:
- en
base_model:
- unsloth/Qwen3-8B-unsloth-bnb-4bit
pipeline_tag: text-generation
library_name: transformers
---
# Model Card for CPA-Qwen3-8B-v0
**CPA-Qwen3-8B-v0** is a specialized large language model developed by **[AudCor](https://huggingface.co/AudCor)**, designed specifically to assist with Certified Public Accountant (CPA) tasks, regulatory compliance, and financial reasoning.
## About AudCor
**AudCor** is dedicated to building advanced AI tools tailored for CPA firms. Our mission is to enhance the productivity and accuracy of accounting professionals by integrating state-of-the-art language models with deep domain expertise in auditing, tax, and financial reporting.
## Key Features
* **CPA Expert Persona:** Fine-tuned to adopt the role of a seasoned CPA, prioritizing accuracy, professional skepticism, and strict adherence to GAAP, IFRS, and tax codes.
* **Domain Specificity:** Optimized for complex financial queries, including audit risk assessment, tax planning strategies, and regulatory interpretation.
* **Exam-Grade Reasoning:** Capable of handling the rigorous logic required for CPA exam-level problems and real-world accounting scenarios.
## CPA Exam Insights
Understanding the standards against which this model is benchmarked requires looking at the rigorous CPA Exam scoring process.
![CPA Pass Rates 2025](https://jobseekertools.com/images/blog/cpa-pass-rates-2025.png)
### The Magic Number: 75
The passing score or "Gold Standard" for the CPA Exam is **75** on a scale of 0-99.
* **Crucial Distinction:** This is a *scaled score*, not a percentage correct.
* **No Curve:** Candidates are measured against a standard of competence, not against each other.
### Scoring Mechanics: Multi-Stage Testing (MST)
The CPA Exam uses an adaptive testing model for Multiple-Choice Questions (MCQs):
1. **Testlet 1:** Always "Medium" difficulty.
2. **Performance Trigger:**
* *Strong Performance* $\rightarrow$ **Testlet 2: Difficult** (Higher scoring potential).
* *Weak Performance* $\rightarrow$ **Testlet 2: Medium** (Lower scoring potential).
> [!NOTE]
> Getting a "Difficult" second testlet is desirable because difficult questions are weighted more heavily, raising your potential score ceiling.
### Section Scoring Breakdown (2025 Update)
With the CPA Evolution changes, the scoring weights have shifted:
| Section Type | MCQ Weight | TBS (Task-Based Simulations) Weight |
| :--- | :--- | :--- |
| **Core Sections (AUD, FAR, REG)** | 50% | 50% |
| **Discipline Sections** | 50% | 50% |
*Data Source: [JobSeekerTools - CPA Passing Score](https://jobseekertools.com/blog/cpa-passing-score)*
## Usage
This model is compatible with `transformers` and `unsloth`.
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "AudCor/cpa-qwen3-8b-v0"
# Load the model
model = AutoModelForCausalLM.from_pretrained(
model_name,
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_name)
# Specialized System Prompt
system_prompt = "You are an expert Certified Public Accountant (CPA). Your goal is to provide accurate, professional, and compliant financial advice..."
messages = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": "Explain the revenue recognition principle under ASC 606."},
]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True).to("cuda")
outputs = model.generate(inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
## Disclaimer
**Not Financial Advice.** This model is an artificial intelligence research tool. While trained on high-quality financial data, it is not a licensed CPA and should not be used as a substitute for professional accounting, tax, or legal advice.
## Citation
```bibtex
@misc{AudCor/cpa-qwen3-8b-v0,
author = {AudCor},
title = {AudCor/cpa-qwen3-8b-v0: A specialized CPA large language model fine-tuned on Josephgflowers/Finance-Instruct-500k},
year = {2025},
publisher = {Hugging Face},
journal = {Hugging Face Model Hub},
howpublished = {\url{https://huggingface.co/AudCor/cpa-qwen3-8b-v0}}
}
```

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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 forward_message in messages %}
{%- set index = (messages|length - 1) - loop.index0 %}
{%- set message = messages[index] %}
{%- set tool_start = '<tool_response>' %}
{%- set tool_start_length = tool_start|length %}
{%- set start_of_message = message.content[:tool_start_length] %}
{%- set tool_end = '</tool_response>' %}
{%- set tool_end_length = tool_end|length %}
{%- set start_pos = (message.content|length) - tool_end_length %}
{%- if start_pos < 0 %}
{%- set start_pos = 0 %}
{%- endif %}
{%- set end_of_message = message.content[start_pos:] %}
{%- if ns.multi_step_tool and message.role == "user" and not(start_of_message == tool_start and end_of_message == tool_end) %}
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{%- endif %}
{%- endfor %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
{%- elif message.role == "assistant" %}
{%- set content = message.content %}
{%- set reasoning_content = '' %}
{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
{%- set reasoning_content = message.reasoning_content %}
{%- else %}
{%- if '</think>' in message.content %}
{%- set content = (message.content.split('</think>')|last).lstrip('\n') %}
{%- set reasoning_content = (message.content.split('</think>')|first).rstrip('\n') %}
{%- set reasoning_content = (reasoning_content.split('<think>')|last).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 }}
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{%- if message.tool_calls %}
{%- for tool_call in message.tool_calls %}
{%- if (loop.first and content) or (not loop.first) %}
{{- '\n' }}
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{%- if tool_call.function %}
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{{- '<tool_call>\n{"name": "' }}
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{%- if tool_call.arguments is string %}
{{- tool_call.arguments }}
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{%- 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 %}
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{{- message.content }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
{{- '<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- if enable_thinking is defined and enable_thinking is false %}
{{- '<think>\n\n</think>\n\n' }}
{%- endif %}
{%- endif %}

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}

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special_tokens_map.json Normal file
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{
"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
}
}

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tokenizer.json (Stored with Git LFS) Normal file

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241
tokenizer_config.json Normal file
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{
"add_bos_token": false,
"add_prefix_space": false,
"added_tokens_decoder": {
"151643": {
"content": "<|endoftext|>",
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"normalized": false,
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"single_word": false,
"special": true
},
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},
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"special": true
},
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"single_word": false,
"special": true
},
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"single_word": false,
"special": true
},
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},
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},
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},
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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 forward_message in messages %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- set message = messages[index] %}\n {%- set tool_start = '<tool_response>' %}\n {%- set tool_start_length = tool_start|length %}\n {%- set start_of_message = message.content[:tool_start_length] %}\n {%- set tool_end = '</tool_response>' %}\n {%- set tool_end_length = tool_end|length %}\n {%- set start_pos = (message.content|length) - tool_end_length %}\n {%- if start_pos < 0 %}\n {%- set start_pos = 0 %}\n {%- endif %}\n {%- set end_of_message = message.content[start_pos:] %}\n {%- if ns.multi_step_tool and message.role == \"user\" and not(start_of_message == tool_start and end_of_message == tool_end) %}\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.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set content = message.content %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is defined and message.reasoning_content is not none %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '</think>' in message.content %}\n {%- set content = (message.content.split('</think>')|last).lstrip('\\n') %}\n {%- set reasoning_content = (message.content.split('</think>')|first).rstrip('\\n') %}\n {%- set reasoning_content = (reasoning_content.split('<think>')|last).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 {{- message.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 {%- if enable_thinking is defined and enable_thinking is false %}\n {{- '<think>\\n\\n</think>\\n\\n' }}\n {%- endif %}\n{%- endif %}"
}

1
vocab.json Normal file

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