use another kind of gradio interface

app.py

@@ -1,6 +1,4 @@
 import gradio as gr
-import torch
-from tqdm import tqdm
 import re
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
@@ -12,47 +10,28 @@ tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
 
 def summarize(text):
+    text = WHITESPACE_HANDLER(text)
     
-    input_ids = tokenizer(
-        [WHITESPACE_HANDLER(text)],
-        return_tensors="pt",
-        padding="max_length",
-        truncation=True,
-        max_length=512
-    )["input_ids"]
-
-    output_ids = model.generate(
-        input_ids=input_ids,
-        max_length=84,
-        no_repeat_ngram_size=2,
-        num_beams=4
-    )[0]
-
-    summary = tokenizer.decode(
-        output_ids,
-        skip_special_tokens=True,
-        clean_up_tokenization_spaces=False
-    )
+    inputs = tokenizer(text, 
+                max_length=1024, 
+                truncation=True,
+                return_tensors="pt")
+
+    summary_ids = model.generate(inputs["input_ids"])
+    summary = tokenizer.batch_decode(summary_ids, 
+                                    skip_special_tokens=True, 
+                                    clean_up_tokenization_spaces=False)
     return summary
 
 
-
-demo = gr.Blocks(title="⭐ Summ4rizer ⭐")
-demo.encrypt = False
-
-with demo:
-    gr.Markdown(f'''
-                <div>
-                <h1 style='text-align: center'>Text Summarizer</h1>
-                </div>
-                <div>
-                Using summarization Model from <a href='https://huggingface.co/{MODEL_NAME}' target='_blank'><b>{MODEL_NAME}</b></a>.
-                </div>
-                ''')
-    text = gr.Textbox(label="Text here !!", lines=1, interactive=True)
-    summarize_btn = gr.Button("Let's Summarize",)
-    summarization = gr.Textbox()
-    html_output = gr.Markdown()
-    summarize_btn.click(summarize, [text], outputs=[html_output, summarization])
+demo = gr.Interface(fn = summarize,
+                        inputs = [gr.inputs.Textbox(lines=10, 
+                                                    placeholder="Inpuy something...",
+                                                    label='Text here !!')],
+                        outputs = [gr.outputs.Textbox(
+                                                      label="Summary")],
+                         
+                        title = "🎈 Summarizer 🎈",
+                        enable_queue=True)
 
 demo.launch()

requirements.txt

@@ -1,4 +1,5 @@
 gradio
 torch
 tqdm
-transformers
+transformers
+sentencepiece