MahmutCanBoran/audi-insight-ai

Audi Insight AI 🚗🔧

Model Description

This model is a fine-tuned mBART-50 sequence-to-sequence model for diagnosing chronic issues in Audi vehicles.
It maps user input describing symptoms (engine, transmission, electrical, etc.) into technical explanations.

The model focuses on Audi models, engine types, and powertrains — helping identify issues such as timing chain problems, turbocharger failures, injector issues, DPF clogging, and more.

Dataset

• Collected from Audi models and known chronic problems
• Training pairs: user complaint (input) → technical explanation (target)

Usage Example

Provide the car model, engine type, power (if relevant), and the observed problem.
The AI Agent will generate a possible technical explanation.

from transformers import MBartForConditionalGeneration, MBart50TokenizerFast

repo_id = "MahmutCanBoran/audi-insight-ai"
tokenizer = MBart50TokenizerFast.from_pretrained(repo_id)
tokenizer.src_lang = "en_XX"
tokenizer.tgt_lang = "en_XX"

model = MBartForConditionalGeneration.from_pretrained(repo_id)

# Example input
inp = "Audi A5 2.0 TFSI,I hear a rattling noise at startup."
enc = tokenizer(inp, return_tensors="pt").to(model.device)

gen = model.generate(
    **enc,
    max_new_tokens=64,
    num_beams=4,
    forced_bos_token_id=tokenizer.lang_code_to_id[tokenizer.tgt_lang]
)

print(tokenizer.decode(gen[0], skip_special_tokens=True))