Update README.md

README.md

@@ -48,7 +48,7 @@ Please give a like and leave a comment if you find this model helpful. I am in a
 ## ✏️Examples
 Educational value is [0, 2]. Detailed formula is explained below.
 ```python
-predict_education_value(['''Logic is the study of correct reasoning. It includes both formal and informal logic. Formal logic is the study of deductively valid inferences or logical truths. It examines how conclusions follow from premises due to the structure of arguments alone, independent of their topic and content. Informal logic is associated with informal fallacies, critical thinking, and argumentation theory. It examines arguments expressed in natural language while formal logic uses formal language. When used as a countable noun, the term "a logic" refers to a logical formal system that articulates a proof system. Logic plays a central role in many fields, such as philosophy, mathematics, computer science, and linguistics.'''])
+predict_educational_value(['''Logic is the study of correct reasoning. It includes both formal and informal logic. Formal logic is the study of deductively valid inferences or logical truths. It examines how conclusions follow from premises due to the structure of arguments alone, independent of their topic and content. Informal logic is associated with informal fallacies, critical thinking, and argumentation theory. It examines arguments expressed in natural language while formal logic uses formal language. When used as a countable noun, the term "a logic" refers to a logical formal system that articulates a proof system. Logic plays a central role in many fields, such as philosophy, mathematics, computer science, and linguistics.'''])
 # Output [1.9266871362924576]
 predict_educational_value(['''"Attention Is All You Need" is a landmark[1][2] 2017 research paper authored by eight scientists working at Google, responsible for expanding 2014 attention mechanisms proposed by Bahdanau et al. into a new deep learning architecture known as the transformer. The paper is considered by some to be a founding document for modern artificial intelligence, as transformers became the main architecture of large language models.[3][4] At the time, the focus of the research was on improving Seq2seq techniques for machine translation, but even in their paper the authors saw the potential for other tasks like question answering and for what is now called multimodal Generative AI.[5]'''])
 # Output [1.8226698189973831]