Update README.md

README.md

@@ -1,15 +1,16 @@
-
 ---
 tags:
 - bertopic
 library_name: bertopic
 pipeline_tag: text-classification
+license: gpl-3.0
 ---
 
 # topic_immigration_it
 
-This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model. 
-BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets. 
+This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model built as part of the European project [VALAWAI](www.valawai.eu) and designed for predicting the topic distribution of immigration-related content in Italian language.<br>
+The model includes a pointer towards the model to be loaded in with SentenceTransformers, i.e., "sentence-transformers/paraphrase-multilingual-mpnet-base-v2".<br>
+The model was fine-tuned on a comprehensive set of tweets representing the information provided by both political entities and news sources on the immigration subject during the 5-year period 2018-2022. 
 
 ## Usage 
 
@@ -26,6 +27,9 @@ from bertopic import BERTopic
 topic_model = BERTopic.load("brema76/topic_immigration_it")
 
 topic_model.get_topic_info()
+
+example_text = "Questo è un esempio di testo sul topic immigrazione, subtopic sbarchi e accoglienza."
+topics, probs = topic_model.transform(example_text)
 ```
 
 ## Topic overview
@@ -100,4 +104,4 @@ topic_model.get_topic_info()
 * Transformers: 4.33.1
 * Numba: 0.56.4
 * Plotly: 5.16.1
-* Python: 3.10.11
+* Python: 3.10.11