Edit model card

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())
Downloads last month
3
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train Gaurav2k/IMDB_Recommender