Update app.py

app.py

@@ -25,28 +25,32 @@ def top_k_top_p_filtering( logits, top_k=0, top_p=0.0, filter_value=-float('Inf'
         logits[indices_to_remove] = filter_value
     return logits
 
+def generate0(input_text):
+    input_ids = [tokenizer.cls_token_id]
+    input_ids.extend( tokenizer.encode(input_text + "-", add_special_tokens=False) )
+    input_ids = torch.tensor( [input_ids] )
+
+    generated = []
+    for _ in range(100):
+        output = model(input_ids)
+
+        next_token_logits = output.logits[0, -1, :]
+        next_token_logits[ tokenizer.convert_tokens_to_ids('[UNK]') ] = -float('Inf')
+        filtered_logits = top_k_top_p_filtering(next_token_logits, top_k=8, top_p=1)
+        next_token = torch.multinomial( F.softmax(filtered_logits, dim=-1), num_samples=1 )
+        if next_token == tokenizer.sep_token_id:
+            break
+        generated.append( next_token.item() )
+        input_ids = torch.cat( (input_ids, next_token.unsqueeze(0)), dim=1 )
+
+    return "".join( tokenizer.convert_ids_to_tokens(generated) )
+    
 def generate(input_text):
-    result = []
-    for i in range(0,5):
-        generated = []
-        for _ in range(100):
-            input_ids = [tokenizer.cls_token_id]
-            input_ids.extend( tokenizer.encode(input_text + "-", add_special_tokens=False) )
-            input_ids = torch.tensor( [input_ids] )
-
-            output = model(input_ids)
-
-            next_token_logits = output.logits[0, -1, :]
-            next_token_logits[ tokenizer.convert_tokens_to_ids('[UNK]') ] = -float('Inf')
-            filtered_logits = top_k_top_p_filtering(next_token_logits, top_k=8, top_p=1)
-            next_token = torch.multinomial( F.softmax(filtered_logits, dim=-1), num_samples=1 )
-            if next_token == tokenizer.sep_token_id:
-                break
-            generated.append( next_token.item() )
-            input_ids = torch.cat( (input_ids, next_token.unsqueeze(0)), dim=1 )
-        result.append("".join(tokenizer.convert_ids_to_tokens(generated)));
-            
-    return "|".join( result )
+    result = [] 
+    for i in range(100):
+        text = generate0(input_text)
+        result.append(text)
+    return "".join( result )
 
 if __name__ == "__main__":
 
@@ -54,5 +58,4 @@ if __name__ == "__main__":
         fn=generate,
         inputs="text",
         outputs="text"
-    ).launch()
-
+    ).launch()