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