Update app.py

app.py

@@ -36,19 +36,17 @@ with st.spinner(text="Please wait while the model is loading...."):
     tokenizer = load_tokenizer('nafisehNik/girt-t5-base')
 
 
-def compute(sample, num_beams, length_penalty, early_stopping, max_length, min_length):
+def compute(sample, top_p, top_k, do_sample, max_length, min_length):
 
     inputs = tokenizer(sample, return_tensors="pt").to('cpu')
 
     outputs = model.generate(
         **inputs,
-        num_beams=num_beams,
-        num_return_sequences=1,
-        length_penalty=length_penalty,
-        no_repeat_ngram_size=2,
-        early_stopping=early_stopping,
+        min_length= min_length,
         max_length=max_length,
-        min_length=min_length).to('cpu')
+        do_sample=do_sample,
+        top_p=top_p,
+        top_k=top_k).to('cpu')
 
     generated_texts = tokenizer.batch_decode(outputs, skip_special_tokens=False)
     generated_text = generated_texts[0]
@@ -83,12 +81,14 @@ with tab2:
     sent = st.text_input(
         "Sentence:", placeholder="Enter a prompt.", on_change=None
     )
-
+    
     # TODO: Check if this is needed!
     clicked = st.button("Submit")
 
-    if sent:
-        res = compute(sent, num_beams=2, length_penalty=1.0, early_stopping=True, max_length=300, min_length=20)
-        st.code(res, language="python")
+    with st.spinner("Please Wait..."):
+
+        if sent:
+            res = compute(sent, top_p=0.92, top_k=0, do_sample=True, max_length=512, min_length=0)
+            st.code(res, language="python")