GCC Intent Classifier v2
Built by OCG Dubai — Agentic Commerce APIs for the GCC
A text classification model for detecting customer intents in GCC e-commerce conversations. Supports English and Arabic queries across common retail interaction patterns.
Intents
| Intent | Example |
|---|---|
product_search |
"Show me gold jewelry under 500 AED" |
order_status |
"Where is my order?" |
return_request |
"I want to return this item" |
price_inquiry |
"How much is the Samsung S24?" |
complaint |
"The delivery was late" |
recommendation |
"What do you suggest for Eid gifts?" |
store_info |
"What are your opening hours?" |
payment_help |
"Can I pay with Tamara?" |
Usage
from transformers import pipeline
classifier = pipeline("text-classification", model="GencoDiv/intent-classifier-gcc-v2")
result = classifier("I want to return the shoes I bought yesterday")
# [{'label': 'return_request', 'score': 0.95}]
Status
⚠️ Model weights pending upload. This card documents the intended architecture and training plan. Model files will be uploaded after fine-tuning on GCC e-commerce conversation data.
Training Plan
- Base model:
distilbert-base-multilingual-cased - Fine-tuning data: GCC e-commerce customer service logs (anonymized)
- Languages: English + Gulf Arabic
- Target accuracy: >90% on held-out test set