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Chiraag-P-V/E-commerce-customer-query-classifier
E-commerce-customer-query-classifier is a text classification model from Chiraag-P-V. Use it when you need a label for a piece of text. The card lists the license as mit.
This model is a fine-tuned version of distilbert-base-uncased for classifying e-commerce customer complaints and queries into multiple categories. It was trained on the Ataur77/ecommerce-customer-support dataset and c…
Downloads · 30 days
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From the Hugging Face model README
This model is a fine-tuned version of distilbert-base-uncased for classifying e-commerce customer complaints and queries into multiple categories.
It was trained on the Ataur77/ecommerce-customer-support dataset and can identify a wide range of e-commerce support issues.
The goal is to help customer service teams automatically route tickets to the correct department for faster resolution.
The model can classify queries into the following 15 categories:
| Label ID | Category |
|---|---|
| 0 | Account & Shipping |
| 1 | Promotions |
| 2 | Payments |
| 3 | Order Tracking |
| 4 | Technical Issues |
| 5 | Product Issues |
| 6 | Refunds |
| 7 | Order Issues |
| 8 | Subscriptions |
| 9 | Checkout |
| 10 | Inventory |
| 11 | Product Quality |
| 12 | Returns |
| 13 | Account |
| 14 | Shipping |
| 15 | Special Requests |
Limitations
from transformers import pipeline
# Load the model from Hugging Face
classifier = pipeline(
"text-classification",
model="Chiraag-P-V/E-commerce-customer-query-classifier"
)
# Example query
query = "I have not received my delivery yet."
result = classifier(query)
print(result)