Here’s a simple example using Python and the transformers library for generating a plot summary embedding:
from transformers import BertTokenizer, BertModel
import torch
# Example plot summary
plot_summary = "A modern retelling of the classic Seven Samurai story, set in India."
# Load pre-trained model and tokenizer
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = BertModel.from_pretrained('bert-base-uncased')
# Preprocess text
inputs = tokenizer(plot_summary, return_tensors="pt")
# Generate embedding
outputs = model(**inputs)
plot_embedding = outputs.last_hidden_state[:, 0, :] # Take CLS token embedding
# Further processing or use in your application
print(plot_embedding.shape)
For a movie, features can range from simple metadata to complex, deep-learned representations. Here are some features that could be considered: the glorious seven 2019 dual audio hindi mkv upd
Genre Classification:
Sentiment Analysis: