Update README.md

README.md

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     biomedical domains and news texts. We explore the role of transfer learning
     between different domains to improve the model performance on small text
     corpora.
-- text: >-
-    <|KEYPHRASES|> Relevance has traditionally been linked with feature subset
-    selection, but formalization of this link has not been attempted. In this
-    paper, we propose two axioms for feature subset selection sufficiency axiom
-    and necessity axiombased on which this link is formalized: The expected
-    feature subset is the one which maximizes relevance. Finding the expected
-    feature subset turns out to be NP-hard. We then devise a heuristic algorithm
-    to find the expected subset which has a polynomial time complexity. The
-    experimental results show that the algorithm finds good enough subset of
-    features which, when presented to C4.5, results in better prediction
-    accuracy.
-- text: >-
-    <|TITLE|> Relevance has traditionally been linked with feature subset
-    selection, but formalization of this link has not been attempted. In this
-    paper, we propose two axioms for feature subset selection sufficiency axiom
-    and necessity axiombased on which this link is formalized: The expected
-    feature subset is the one which maximizes relevance. Finding the expected
-    feature subset turns out to be NP-hard. We then devise a heuristic algorithm
-    to find the expected subset which has a polynomial time complexity. The
-    experimental results show that the algorithm finds good enough subset of
-    features which, when presented to C4.5, results in better prediction
-    accuracy.
 library_name: transformers
 pipeline_tag: text2text-generation
 ---