Update README.md

README.md

@@ -43,7 +43,7 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-This is a multi-class classifier of Russian news, made with the LaBSE model finetune for (AntiSMI Project)[https://github.com/data-silence/antiSMI-Project]. 
+This is a multi-class classifier of Russian news, made with the LaBSE model finetune for [AntiSMI Project](https://github.com/data-silence/antiSMI-Project). 
 The news category is assigned by the classifier to one of 11 categories:
 - climate (климат)
 - conflicts (конфликты)
@@ -57,6 +57,41 @@ The news category is assigned by the classifier to one of 11 categories:
 - sports (спорт)
 - travel (путешествия)
 
+## How to use
+
+```
+python
+
+from transformers import pipeline
+
+category_mapper = {
+'LABEL_0': 'climate',
+'LABEL_1': 'conflicts',
+'LABEL_2': 'culture',
+'LABEL_3': 'economy',
+'LABEL_4': 'gloss',
+'LABEL_5': 'health',
+'LABEL_6': 'politics',
+'LABEL_7': 'science',
+'LABEL_8': 'society',
+'LABEL_9': 'sports',
+'LABEL_10': 'travel'
+}
+
+# Используйте предобученную модель из Hugging Face Hub
+classifier = pipeline("text-classification", model="data-silence/rus-news-classifier")
+
+def predict_category(text):
+    result = classifier(text)
+    category = category_mapper[result[0]['label']]
+    score = result[0]['score']
+    return category, score
+
+predict_category("В Париже завершилась церемония закрытия Олимпийских игр")
+# ('sports', 0.9959506988525391)
+```
+
+
 ## Intended uses & limitations
 
 Enjoy to use in your purpose