Gaurav2k/IMDB_Recommender

Model Card

Model Description

This model is a movie recommender system trained on IMDB movie data. It provides movie recommendations based on cosine similarity of text features extracted from movie titles and other attributes.

Intended Use

• Recommendation: The model is designed to recommend movies based on a given movie title. It provides a list of similar movies from the IMDB dataset.

How to Use

1. Input: Provide a movie title as input.
2. Output: The model returns a list of recommended movies based on similarity.

Model Details

• Training Data: The model was trained on a dataset of IMDB movies including movie titles, genres, and other attributes.
• Features: The model uses text features extracted from movie titles and additional metadata such as genres and certificates.

Example

To get recommendations, you can use the following code snippet:

import requests

model_name = 'Gaurav2k/IMDB_Recommender'
api_url = f'https://api-inference.huggingface.co/models/{model_name}'
headers = {
    'Authorization': f'Bearer your_token'
}
data = {
    'inputs': 'The Godfather'
}

response = requests.post(api_url, headers=headers, json=data)
print(response.json())