metadata
dataset_info:
features:
- name: runtime
dtype: float64
- name: languages
sequence: string
- name: metacritic
dtype: float64
- name: type
dtype: string
- name: imdb
struct:
- name: id
dtype: int64
- name: rating
dtype: float64
- name: votes
dtype: int64
- name: genres
sequence: string
- name: awards
struct:
- name: nominations
dtype: int64
- name: text
dtype: string
- name: wins
dtype: int64
- name: rated
dtype: string
- name: cast
sequence: string
- name: directors
sequence: string
- name: fullplot
dtype: string
- name: title
dtype: string
- name: num_mflix_comments
dtype: int64
- name: countries
sequence: string
- name: plot
dtype: string
- name: poster
dtype: string
- name: writers
sequence: string
- name: plot_embedding
sequence: float64
splits:
- name: train
num_bytes: 13657438
num_examples: 1452
download_size: 10625884
dataset_size: 13657438
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
This dataset originates from MongoDB's embedded_movies dataset and contains details on movies from different genres. Each row represents a single movie with detailed information.
As opposed to the original dataset, this one includes embeddings of the fullplot column using the open source General Text Embeddings model instead of OpenAI's text-embedding-ada-002 embedding model used in MongoDB Atlas.
Those open source embeddings are also used in Hermes.