Added news title generation

app.py

@@ -109,6 +109,14 @@ def summarize(input, model_choice, max_new_tokens, length_penalty, no_repeat_ngr
     summarization_model = pipeline(model=model_mapping[model_choice], device=0) 
     return summarization_model(input, max_new_tokens = max_new_tokens, length_penalty=length_penalty, no_repeat_ngram_size=no_repeat_ngram_size)[0]["generated_text"]
 
+@spaces.GPU    
+def generate_title(input, model_choice, max_new_tokens, length_penalty, no_repeat_ngram_size):
+    model_mapping = {"turna_title_generation_tr_news": "boun-tabi-LMG/turna_title_generation_tr_news",
+                     "turna_title_generation_mlsum": "boun-tabi-LMG/turna_title_generation_mlsum"}
+    summarization_model = pipeline(model=model_mapping[model_choice], device=0) 
+    return summarization_model(input, max_new_tokens = max_new_tokens, length_penalty=length_penalty, no_repeat_ngram_size=no_repeat_ngram_size)[0]["generated_text"]
+
+
 @spaces.GPU
 def categorize(input):
     ttc = pipeline(model="boun-tabi-LMG/turna_classification_ttc4900", device=0) 
@@ -241,6 +249,30 @@ with gr.Blocks(theme="abidlabs/Lime") as demo:
                 sum_submit.click(summarize, inputs=[sum_input, sum_choice, max_new_tokens, length_penalty, no_repeat_ngram_size], outputs=sum_output)
             sum_examples = gr.Examples(examples = long_text, inputs = [sum_input, sum_choice, max_new_tokens, length_penalty, no_repeat_ngram_size], outputs=sum_output,  fn=summarize)
     
+    with gr.Tab("Title Generation"):
+        gr.Markdown("TURNA fine-tuned on news title generation. Enter news text to generate a title.")
+        with gr.Column():
+            with gr.Row():
+                with gr.Column():
+                    title_choice = gr.Radio(choices = ["turna_title_generation_tr_news", "turna_title_generation_mlsum"], label ="Model", value="turna_title_generation_tr_news")
+                    with gr.Accordion("Advanced Generation Parameters"):
+                        max_new_tokens = gr.Slider(label = "Maximum length",
+                        		minimum = 0,
+                        		maximum = 64,
+                        		value = 64)
+                        length_penalty = gr.Slider(label = "Length penalty",
+                                    minimum = -10,
+                        		    maximum = 10,
+                            		value=2.0)
+                        no_repeat_ngram_size =gr.Slider(label="No Repeat N-Gram Size", minimum=0,value=3,)
+                with gr.Column():
+                    title_input = gr.Textbox(label = "News Title Generation Input")
+                    title_submit = gr.Button()
+                title_output = gr.Textbox(label = "News Title Generation Output")
+                
+                title_submit.click(generate_title, inputs=[title_input, title_choice, max_new_tokens, length_penalty, no_repeat_ngram_size], outputs=title_output)
+            title_examples = gr.Examples(examples = long_text, inputs = [title_input, title_choice, max_new_tokens, length_penalty, no_repeat_ngram_size], outputs=title_output,  fn=generate_title)
+
     with gr.Tab("Text Generation"):
         gr.Markdown("Pre-trained TURNA. Enter text to start generating.")
         with gr.Column():