removed disfunctional share buttons

app.py

@@ -109,12 +109,14 @@ def instantiate_chatbots(sel1, sel2):
     chatbot1 = gr.Chatbot(
         type="messages",
         show_label=False,
+        show_share_button=False,
         avatar_images=("img/usr.png", bot_icon_select(model_name1)),
     )
     model_name2 = model_presets[sel2]
     chatbot2 = gr.Chatbot(
         type="messages",
         show_label=False,
+        show_share_button=False,
         avatar_images=("img/usr.png", bot_icon_select(model_name2)),
     )
     return chatbot1, chatbot2
@@ -163,6 +165,7 @@ with gr.Blocks(fill_width=True, title="Keras demo") as demo:
             show_label=False,
             show_download_button=False,
             show_fullscreen_button=False,
+            show_share_button=False,
             interactive=False,
             scale=0.01,
             container=False,
@@ -171,8 +174,8 @@ with gr.Blocks(fill_width=True, title="Keras demo") as demo:
             "<H2> Battle of the Keras chatbots on TPU</H2>"
             + "All the models are loaded into the TPU memory. "
             + "You can call any of them and compare their answers. <br/>"
-            + "The entire chat history is fed to the models at every submission."
-            + "This demno is runnig on a Google TPU v5e 2x4 (8 cores).",
+            + "The entire chat history is fed to the models at every submission. "
+            + "This demo is runnig on a Google TPU v5e 2x4 (8 cores).",
         )
     with gr.Row():
         sel1, sel2 = instantiate_select_boxes(0, 1, model_labels_list)
@@ -180,9 +183,8 @@ with gr.Blocks(fill_width=True, title="Keras demo") as demo:
     with gr.Row():
         chatbot1, chatbot2 = instantiate_chatbots(sel1.value, sel2.value)
 
-    msg = gr.Textbox(
-        label="Your message:",
-    )
+    msg = gr.Textbox(label="Your message:", submit_btn=True)
+
     with gr.Row():
         gr.ClearButton([msg, chatbot1, chatbot2])
         with gr.Accordion("Additional settings", open=False):

models.py

@@ -44,6 +44,7 @@ def log_applied_layout_map(model):
     else:  # works for Llama, Mistral, Vicuna
         transformer_decoder_block_name = "transformer_layer_1"
 
+    print("Model class:", type(model).__name__)
     # See how layer sharding was applied
     embedding_layer = model.backbone.get_layer("token_embedding")
     print(embedding_layer)