Update app.py

app.py

@@ -28,6 +28,11 @@ st.sidebar.markdown(
     text-align: center;
 }
 </style>
+<p class="aligncenter">
+    <a href="https://github.com/AlekseyKorshuk/huggingartists" target="_blank"> 
+        <img src="https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social"/>
+    </a>
+</p>
 <p style='text-align: center'>
 <a href="https://github.com/AlekseyKorshuk/huggingartists" target="_blank">GitHub</a> | <a href="https://wandb.ai/huggingartists/huggingartists/reportlist" target="_blank">Project Report</a>
 </p>
@@ -41,24 +46,24 @@ st.sidebar.markdown(
 )
 
 
-st.sidebar.header("SELECT YOUR VIEW DIRECTION")
+st.sidebar.header("SETTINGS")
 num_sequences = st.sidebar.number_input(
     "Number of sequences to generate",
     min_value=1,
     value=5,
-    help="Amount of generated texts",
+    help="The amount of generated texts",
 )
 min_length = st.sidebar.number_input(
     "Minimum length of the sequence",
     min_value=1,
     value=100,
-    help="Minimum length of the sequence",
+    help="The minimum length of the sequence to be generated",
 )
 max_length= st.sidebar.number_input(
     "Maximum length of the sequence",
     min_value=1,
     value=160,
-    help="Maximum length of the sequence",
+    help="The maximum length of the sequence to be generated",
 )
 temperature = st.sidebar.slider(
     "Temperature",
@@ -66,34 +71,29 @@ temperature = st.sidebar.slider(
     max_value=3.0,
     step=0.01,
     value=1.0,
-    help="Temperature",
+    help="The value used to module the next token probabilities",
 )
 top_p = st.sidebar.slider(
-    "Top P",
+    "Top-P",
     min_value=0.0,
     max_value=1.0,
     step=0.01,
     value=0.95,
-    help="Top P",
+    help="If set to float < 1, only the most probable tokens with probabilities that add up to top_p or higher are kept for generation.",
 )
 
 top_k= st.sidebar.number_input(
-    "Top K",
+    "Top-K",
     min_value=0,
     value=50,
     step=1,
-    help="Top K",
+    help="The number of highest probability vocabulary tokens to keep for top-k-filtering.",
 )
 
 caption = (
-    "`DietNeRF` achieves state-of-the-art few-shot learning capacity in 3D model reconstruction. "
-    "Thanks to the 2D supervision by `CLIP (aka. Semantic Consisteny Loss)`, "
-    "it can render novel and challenging views with `ONLY 8 training images`, "
-    "**outperforming** original [NeRF](https://www.matthewtancik.com/nerf)!"
+    "`HuggingArtists` - Train a model to generate lyrics"
+    ""
+    "In HuggingArtists, we can generate lyrics by a specific artist. This was made by fine-tuning a pre-trained HuggingFace Transformer on parsed datasets from Genius."
 )
 st.markdown(caption)
-st.markdown(
-    "> 📒 **NOTE**: To get a detailed comparison of differences in results between `DietNeRF` and `NeRF`, you can take a look at the "
-    "[Experimental Results](https://www.notion.so/DietNeRF-Putting-NeRF-on-a-Diet-4aeddae95d054f1d91686f02bdb74745#0f6bc8f1008d4765b9b4635999626d4b) "
-    "section in our project report."
-)
+