Parameter check

app.py

@@ -15,12 +15,15 @@ def run_prediction(sample, model, processor, mode):
         no_repeat_ngram_size = 10
     elif mode == "Table":
         prompt = "<s><s_hierarchical>"
-        no_repeat_ngram_size = 45
+        no_repeat_ngram_size = 0
     else:
         prompt = "<s><s_hierarchical>"
         no_repeat_ngram_size = 10
 
 
+    print("prompt:", prompt)
+    print("no_repeat_ngram_size:", no_repeat_ngram_size)
+
     pixel_values = processor(np.array(
                     sample,
                     np.float32,
@@ -32,7 +35,7 @@ def run_prediction(sample, model, processor, mode):
             decoder_input_ids=processor.tokenizer(prompt, add_special_tokens=False, return_tensors="pt").input_ids.to(device),
             do_sample=True,
             top_p=0.92, #.92,
-            top_k=10,
+            top_k=5,
             no_repeat_ngram_size=no_repeat_ngram_size,
             num_beams=3,
             output_attentions=False,
@@ -67,7 +70,7 @@ with st.sidebar:
         image_bytes_data = uploaded_file.getvalue()
         image_upload = Image.open(BytesIO(image_bytes_data))
 
-    mode = st.selectbox('Mode', ('OCR', 'Tables', 'Element annotation'), index=2)
+    mode = st.selectbox('Mode', ('OCR', 'Table', 'Element annotation'), index=2)
 
 if image_upload:
     image = image_upload