Update generation params

app.py

@@ -7,7 +7,7 @@ tokenizer = T5Tokenizer.from_pretrained("rinna/japanese-gpt-1b")
 model = AutoModelForCausalLM.from_pretrained("rinna/japanese-gpt-1b")
 
 
-def generate(text, max_length=128):
+def generate(text, max_length=512):
 
     token_ids = tokenizer.encode(
         text, add_special_tokens=False, return_tensors="pt")
@@ -19,13 +19,14 @@ def generate(text, max_length=128):
             do_sample=True,
             top_k=500,
             top_p=0.95,
-            pad_token_id=tokenizer.pad_token_id,
-            bos_token_id=tokenizer.bos_token_id,
-            eos_token_id=tokenizer.eos_token_id,
-            bad_word_ids=[[tokenizer.unk_token_id]]
+            #pad_token_id=tokenizer.pad_token_id,
+            #bos_token_id=tokenizer.bos_token_id,
+            #eos_token_id=tokenizer.eos_token_id,
+            #bad_word_ids=[[tokenizer.unk_token_id]]
+            early_stopping=False,
         )
 
-    output = tokenizer.decode(output_ids.tolist()[0])
+    output = tokenizer.decode(output_ids.tolist()[0], skip_specual_tokens=True)
     return output, translate_from_jp_to_en(output)
 
 
@@ -33,7 +34,7 @@ title = "JP GPT Demo"
 description = "Demo for generating text in Japanase using a GPT model"
 examples = [['日本のeスポーツ障害者がステレオタイプを撃ち落とす', 128]]
 gr.Interface(fn=generate, inputs=[gr.inputs.Textbox(lines=4, label="Prompt"),
-                                  gr.inputs.Slider(minimum=8, maximum=1024, step=8, default=64, label="Numbers of tokens")],
+                                  gr.inputs.Slider(minimum=8, maximum=4096, step=8, default=64, label="Numbers of tokens")],
              outputs=["text", "text"],
              title=title, description=description,
              # article= article,