AutoCareBrain-3B

Model Description

AutoCareBrain-3B is a specialized large language model designed specifically for the automotive repair and maintenance domain. Built upon the powerful Qwen2.5 foundation model, it has been trained with extensive real-world Q&A data covering multiple core automotive systems including engines, transmissions, electrical systems, chassis, and suspension components. The model is designed to generate detailed chains of thought, providing precise fault diagnosis and repair recommendations to help vehicle owners and technicians quickly identify problems and formulate optimal solutions.

Key Features

Intelligent Repair Q&A: Quickly answers complex questions about vehicle malfunctions, maintenance, and repairs, providing professional and detailed solutions
Precise Fault Diagnosis: Recommends the most likely causes of failure and repair solutions based on multidimensional analysis of vehicle symptoms, improving repair efficiency
Transparent Reasoning Process: Generates detailed chains of thought to ensure the explainability of fault diagnosis and repair recommendations, helping users understand the root causes of problems

Intended Uses

Automotive Repair Shops: Assists technicians with diagnostics and repair procedures
Vehicle Owner Self-Diagnosis: Helps car owners identify potential issues before visiting a repair shop
4S Dealership Service Support: Enhances customer service and technical support capabilities
Automotive Technical Training: Serves as an educational tool for training new automotive technicians

Training Data

AutoCareBrain-3B was trained on a diverse dataset comprising:

Real-world automotive repair Q&A sessions
Technical documentation for various vehicle systems
Repair manuals and service bulletins
Expert knowledge across multiple vehicle makes and models

The model was trained to generate detailed reasoning chains, provide accurate diagnostics, and suggest evidence-based repair procedures.

Technical Specifications

Parameters: 3 billion
Base Model: Qwen2.5
Training Method: Supervised Fine-Tuning (SFT)
Language Capabilities: English, Chinese
Input Format: Natural language queries about automotive issues
Output Format: Detailed explanations with chain-of-thought reasoning and repair recommendations

Limitations

The model should be used as a diagnostic support tool and not as a replacement for professional automotive technician judgment
Recommendations should be verified by qualified automotive professionals
Performance may vary depending on the complexity and rarity of vehicle issues
The model may not have specific information on very recent vehicle models or emerging technologies
While the model supports English and Chinese, performance might vary between languages

Ethical Considerations

Safety: The model provides recommendations that prioritize vehicle safety
Transparency: The model provides reasoning chains to ensure transparency in its decision-making process
Accuracy: While the model strives for accuracy, all critical repairs should be verified by qualified professionals

How to Use

# Example code for model inference
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DXCLab/AutoCareBrain-3B")
model = AutoModelForCausalLM.from_pretrained("DXCLab/AutoCareBrain-3B")

input_text = "My car makes a grinding noise when I apply the brakes, especially when slowing down from highway speeds. What could be the problem and how should I fix it?"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=1000)
response = tokenizer.decode(outputs[0])
print(response)

Citation

If you use AutoCareBrain-3B in your research or applications, please cite:

@misc{AutoCareBrain-3B,
  author = {DXCLab},
  title = {AutoCareBrain-3B: A Specialized Language Model for Automotive Repair and Maintenance},
  year = {2025},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/DXCLab/AutoCareBrain-3B}}
}

License

This model is licensed under the Apache License 2.0. See the LICENSE file for details.

Contact

For questions or feedback about AutoCareBrain-3B, please visit our Hugging Face page at https://huggingface.co/DXCLab or open an issue in the repository.

DXCLab
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AutoCareBrain-3B