Simplify Sentence similarity entry
Remove mention of embedding and stick to just models
@@ -8,10 +8,10 @@ This folder contains examples and best practices, written in Jupyter notebooks,
|[Named Entity Recognition](named_entity_recognition) |Wikipedia NER|BERT|en|
|[Entailment](entailment)|MultiNLI Natural Language Inference|BERT|en|
|[Question Answering](question_answering) |SQuAD|BiDAF, BERT|en|
-|[Sentence Similarity](sentence_similarity)|STS Benchmark|Representation: TF-IDF, Word Embeddings, Doc Embeddings<br>Metrics: Cosine Similarity, Word Mover's Distance<br> Models: BERT, GenSen||
-|[Embeddings](embeddings)|Custom Embeddings Training|Word2Vec, fastText, GloVe||
-|[Annotation](annotation)|Text Annotation|Doccano||
-|[Model Explainability](model_explainability)|DNN Layer Explanation|DUUDNM (Guan et al.)|
+|[Sentence Similarity](sentence_similarity)|STS Benchmark|BERT, GenSen|en|
+|[Embeddings](embeddings)|Custom Embeddings Training|Word2Vec, fastText, GloVe|en|
+|[Annotation](annotation)|Text Annotation|Doccano|en|
+|[Model Explainability](model_explainability)|DNN Layer Explanation|DUUDNM (Guan et al.)|en|
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