---
tags:
- text-classification
- intent-detection
- gcc
- e-commerce
- agentic-commerce
- ocg-dubai
- gulf-retail
language:
- en
- ar
pipeline_tag: text-classification
license: mit
---

# GCC Intent Classifier v2

> Built by [OCG Dubai](https://ocg-dubai.ae) — 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

```python
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