Adding App

app.py

@@ -17,7 +17,7 @@ def load_model():
   return model
     
 st.title("Sentence Embedding for Spanish with Bertin")
-st.write("Sentence embedding for spanish trained according to instructions in the paper [Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation](https://arxiv.org/pdf/2004.09813.pdf) and the [documentation](https://www.sbert.net/examples/training/multilingual/README.html) accompanying its companion python package. We have used the strongest available pretrained English Bi-Encoder ([paraphrase-mpnet-base-v2](https://www.sbert.net/docs/pretrained_models.html#sentence-embedding-models)) as a teacher model, and the pretrained Spanish [BERTIN](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) as the student model.Used for Sentence Textual Similarity. Based on the model hackathon-pln-es/paraphrase-spanish-distilroberta.")
+st.write("Sentence embedding for spanish trained according to instructions in the paper [Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation](https://arxiv.org/pdf/2004.09813.pdf) and the [documentation](https://www.sbert.net/examples/training/multilingual/README.html) accompanying its companion python package. We have used the strongest available pretrained English Bi-Encoder ([paraphrase-mpnet-base-v2](https://www.sbert.net/docs/pretrained_models.html#sentence-embedding-models)) as a teacher model, and the pretrained Spanish [BERTIN](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) as the student model. Used for Sentence Textual Similarity. Based on the model hackathon-pln-es/paraphrase-spanish-distilroberta.")
 st.write("Introduce two sentence to see their cosine similarity and a graph showing them in the embedding space.")
 st.write("Authors: Anibal Pérez, Emilio Tomás Ariza, Lautaro Gesuelli Pinto y Mauricio Mazuecos.")