DistilBERT Intent Classifier for Movie & TV Assistant

This model is a fine-tuned DistilBERT-based intent classifier for a conversational movie recommendation assistant. It classifies user queries into one of three intents:

• generic – general small talk or casual movie mentions
• recommendation – requests for movie or TV suggestions
• factual – questions about movie facts, cast, streaming availability, etc.

Model Details

• Base model: distilbert-base-uncased
• Training data: 6,000+ custom-labeled queries across all 3 intents
• Special augmentations:
  • Out-of-domain recommendation phrasing (e.g. restaurants, gadgets)
  • Thematic recommendation queries (e.g. “movies for Valentine’s Day”)
• Use case: Used inside a RAG-based chatbot for intent-routing and retrieval logic

Example Predictions

Usage

from transformers import pipeline

classifier = pipeline("text-classification", model="your-username/intent-classifier-distilbert-moviebot")

query = "Can you suggest a good action movie?"
result = classifier(query, top_k=None)
print(result)