Исправлен вывод.

app.py

@@ -12,8 +12,25 @@ st.markdown("<p style=\"text-align:center\"><img width=700px src='https://c.teno
 #pipe = pipeline("ner", "Davlan/distilbert-base-multilingual-cased-ner-hrl")
 
 #st.markdown("#### Title:")
-title = st.text_area("Title:")
-abstract = st.text_area("abstract:")
+title = st.text_area("Title:", value="How to cook a neural network", height=16, help="Title of the article")
+abstract = st.text_area("Abstract:",
+    value="""
+          My dad fits hellish models in general.
+          Well, this is about an average recipe, because there are a lot of variations.
+          The model is taken, it is not finetuned, finetuning is not about my dad.
+          He takes this model, dumps it into the tensorboard and starts frying it.
+          Adds a huge amount of noize, convolutions, batch and spectral normalization DROPOUT! for regularization, maxpooling on top.
+          All this is fitted to smoke.
+          Then the computer is removed from the fire and cools on the balcony.
+          Then dad brings it in and generously sprinkles it with crossvalidation and starts predicting.
+          At the same time, he gets data from the web, scraping it with a fork.
+          Predicts and sentences in a half-whisper oh god.
+          At the same time, he has sweat on his forehead.
+          Kindly offers me sometimes, but I refuse.
+          Do I need to talk about what the wildest overfitting then?
+          The overfitting is such that the val loss peels off the walls.
+          """,
+    height=512, help="Abstract of the article")
 
 from transformers import AutoModel, AutoTokenizer
 #from tqdm import tqdm as tqdm
@@ -37,7 +54,7 @@ os.system("python3 -m spacy download en")
 # Но этим займёмся потом, если будет время.
 main_nlp = spacy.load('en_core_web_sm')
 
-text = title + abstract
+text = title + ". " + abstract
 
 if not text is None and len(text) > 0:
     #keywords = get_candidates(text, main_nlp)