Description
A pre-trained pipeline to classify IMDB reviews in neg and pos classes using tfhub_use embeddings.
Live Demo Open in Colab Download Copy S3 URI
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("analyze_sentimentdl_use_imdb", lang = "en")
result = pipeline.fullAnnotate("Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("analyze_sentimentdl_use_imdb", lang = "en")
val result = pipeline.fullAnnotate("Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!")
import nlu
text = ["""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!"""]
sentiment_df = nlu.load('en.sentiment.imdb.use').predict(text, output_level='sentence')
sentiment_df
Results
| | document | sentiment |
|---:|---------------------------------------------------------------------------------------------------------:|--------------:|
| | Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the | |
| 0 | film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music | positive |
| | was rad! Horror and sword fight freaks,buy this movie now! | |
Model Information
| Model Name: | analyze_sentimentdl_use_imdb |
| Type: | pipeline |
| Compatibility: | Spark NLP 2.7.1+ |
| Edition: | Official |
| Language: | en |
Included Models
tfhub_use, sentimentdl_use_imdb