Update app.py

app.py

@@ -72,18 +72,18 @@ def proc_submission(
         msg = None
         
     if (model_type == "LED" and summary_type == "Detailed"):
-        model = model_led_det
+        m = model_led_det
     elif (model_type == "LED" and summary_type == "TLDR"):
-        model = model_led_tldr
+        m = model_led_tldr
     elif (model_type == "LongT5" and summary_type == "Detailed"):
-        model = model_det
+        m = model_det
     else:
-        model = model_tldr
+        m = model_tldr
         #tokenizer_led_det if (model_type == "LED" and summary_type == "Detailed") else tokenizer_det,
     _summaries = summarize_via_tokenbatches(
         tr_in,
         tokenizer_led_det if (model_type == "LED") else tokenizer_det,
-        model = model,
+        model = m,
         batch_length=token_batch_length,
         **settings,
     )
@@ -155,8 +155,8 @@ if __name__ == "__main__":
 
     model_det, tokenizer_det = load_model_and_tokenizer("Blaise-g/longt5_tglobal_large_sumpubmed")
     model_tldr, tokenizer_tldr = load_model_and_tokenizer("Blaise-g/longt5_tglobal_large_scitldr")
-    model_led_det, tokenizer_led_det = load_model_and_tokenizer("Blaise-g/led_pubmed_sumpubmed_1")
-    model_led_tldr, tokenizer_led_tldr = load_model_and_tokenizer("Blaise-g/led_large_sumpbumed_scitldr")
+    #model_led_det, tokenizer_led_det = #load_model_and_tokenizer("Blaise-g/led_pubmed_sumpubmed_1")
+    #model_led_tldr, tokenizer_led_tldr = load_model_and_tokenizer("Blaise-g/led_large_sumpbumed_scitldr")
 
     name_to_path = load_example_filenames(_here / "examples")
     logging.info(f"Loaded {len(name_to_path)} examples")