Update apps/home.py

apps/home.py

@@ -23,6 +23,45 @@ def write():
 			"""
 			<h3 style="text-align:left;">a Turkish encoder-decoder language model</h3>
 			<p style="text-align:right;"><p>
+            """, unsafe_allow_html=True,
+    )
+    st.markdown(
+            """
+Welcome to our Huggingface space, where you can explore the capabilities of TURNA. 
+
+**Key Features of TURNA:**
+
+- **Powerful Architecture:** TURNA contains 1.1B parameters, and was pre-trained with an encoder-decoder architecture following the UL2 framework on 43B tokens from various domains.
+- **Diverse Training Data:** Our model is trained on a varied dataset of 43 billion tokens, covering a wide array of domains.
+- **Broad Applications:** TURNA is fine-tuned for a variety of generation and understanding tasks, including:
+    - Summarization
+    - Paraphrasing
+    - News title generation
+    - Sentiment classification
+    - Text categorization
+    - Named entity recognition
+    - Part-of-speech tagging
+    - Semantic textual similarity
+    - Natural language inference
+
+Explore various applications powered by **TURNA** using the **Navigation** bar.
+
+Refer to our [paper](https://arxiv.org/abs/2401.14373) for more details...
+
+### Citation
+```bibtex
+@misc{uludoğan2024turna,
+      title={TURNA: A Turkish Encoder-Decoder Language Model for Enhanced Understanding and Generation}, 
+      author={Gökçe Uludoğan and Zeynep Yirmibeşoğlu Balal and Furkan Akkurt and Melikşah Türker and Onur Güngör and Susan Üsküdarlı},
+      year={2024},
+      eprint={2401.14373},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+            """)
+    st.markdown(
+            """
 			<p style="text-align:left;">In this Huggingface space, you can test the TURNA language model. </p>
 			<p style="text-align:left;">The model contains 1.1B parameters, and was pre-trained with an encoder-decoder architecture following the UL2 framework on 43B tokens from various domains.  </p>
             <p style="text-align:left;">TURNA was fine-tuned to carry out Turkish summarization, paraphrasing, news title generation, sentiment classification, text categorization, named entity recognition, part-of-speech tagging, semantic textual similarity and natural language inference tasks.  </p>