😀 Sentiment Analysis
Sentiment Analysis skill with 🔘 Select to classify the polarity of a given text.
sentiment_analysis skill is designed to classify text as negative, neutral, or positive.
It uses the 🔘 Select endpoint, which requires you to specific
candidates that are used for classification. In order to use the skill, the
candidates need to be:
["-", "0", "+"],
-if the expressed opinion is negative,
0if it is neutral,
+if it is positive.
In this short guide, learn how to use the
sentiment_analysis skill with
lyra-en. We assume here that the reader is familiar with the parameters of Select, as well as with the Python Bindings: for more information, check out the 🔘 Select, and Python Bindings documentation pages. We start by initializing the client with the following code.
We start by initializing the client with
from lightonmuse import Select
selector = Select("lyra-en")
From there, using the skill is straightforward:
output = selector("The video you showed me really got me scared", ["-", "+", "0"], skill="sentiment_analysis",)
returns, as expected
while a more neutral prompt
output = selector("Mary told John to check his mailbox", ["-", "+", "0"], skill="sentiment_analysis",)
Good luck classifying your own text!