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Model: AudCor/cpa-qwen3-8b-v0 Source: Original Platform
2026-09-08 17:42:31 +08:00
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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}}
+}
+```