Update app.py

app.py

@@ -41,17 +41,34 @@ def proc_submission(
         str in HTML format, string of the summary, str of score
     """
 
-    settings = {
+    settings_det = {
         "length_penalty": float(length_penalty),
         "repetition_penalty": 3.5,
         "no_repeat_ngram_size": 3,
         "encoder_no_repeat_ngram_size": 4,
         "num_beams": int(num_beams),
-        "min_length": 4,
-        "max_length": int(token_batch_length // 4),
+        "min_length": 100,
+        "max_length": 512,#int(token_batch_length // 4),
         "early_stopping": True,
         "do_sample": False,
     }
+    settings_tldr = {
+        "length_penalty": float(length_penalty),
+        "repetition_penalty": 3.5,
+        "no_repeat_ngram_size": 3,
+        "encoder_no_repeat_ngram_size": 4,
+        "num_beams": int(num_beams),
+        "min_length": 11,
+        "max_length": 62,
+        "early_stopping": True,
+        "do_sample": False,
+    }
+    
+    if model_size == "tldr":
+        settings = settings_tldr
+    else:
+        settings = settings_det
+    
     st = time.perf_counter()
     history = {}
     clean_text = clean(input_text, lower=False)
@@ -169,7 +186,7 @@ if __name__ == "__main__":
                     value=2,
                 )
             gr.Markdown(
-                "_The base model is less performant than the large model, but is faster and will accept up to 2048 words per input (Large model accepts up to 768)._"
+                "_The tldr model variant takes less time to produce the summaries and accepts a longer input sequence all other parameters being equal._"
             )
             with gr.Row():
                 length_penalty = gr.inputs.Slider(