checking qa generator

app.py

@@ -15,7 +15,7 @@ def run_model(input_string, **generator_args):
     input_ids = tokenizer.encode(input_string, return_tensors="pt")
     res = model.generate(input_ids, **generator_args)
     output = tokenizer.batch_decode(res, skip_special_tokens=True)
-    # print(output)
+    print(output)
     return output
 
 
@@ -29,18 +29,13 @@ sent = st.text_area("Text", default_value, height = 150)
 max_length = st.sidebar.slider("Max Length", min_value = 10, max_value=50)
 temperature = st.sidebar.slider("Temperature", value = 1.0, min_value = 0.0, max_value=1.0, step=0.05)
 num_return_sequences = st.sidebar.slider("Num Return Sequences", min_value = 1, max_value=4, value = 1)
-num_beams = st.sidebar.slider("Num Beams", min_value = 4, max_value=10, value = 4)
+num_beams = st.sidebar.slider("Num Beams", min_value = 1, max_value=10, value = 4)
 top_k = st.sidebar.slider("Top-k", min_value = 0, max_value=100, value = 90)
 top_p = st.sidebar.slider("Top-p", min_value = 0.0, max_value=1.0, step = 0.05, value = 0.9)
 
-encoded_prompt = tokenizer.encode(sent, add_special_tokens=False, return_tensors="pt")
-if encoded_prompt.size()[-1] == 0:
-    input_ids = None
-else:
-    input_ids = encoded_prompt
 
 
-output_sequences = run_model(input_ids, max_length=max_length,num_return_sequences=num_return_sequences,
+output_sequences = run_model(sent, max_length=max_length,num_return_sequences=num_return_sequences,
                         num_beams=num_beams,
                         temperature=temperature, top_k=top_k, top_p=top_p)