Update app.py

app.py

@@ -1,40 +1,40 @@
-# app.py
-
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from transformers import T5ForConditionalGeneration, T5Tokenizer
 
-model_name = "Vamsi/T5_Paraphrase_Paws"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+# Load the model
+model_name = "ramsrigouthamg/t5_paraphraser"
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+model = T5ForConditionalGeneration.from_pretrained(model_name)
 
-def paraphrase(text):
+def paraphrase_text(text):
     if not text.strip():
-        return "No input provided."
-
-    input_ids = tokenizer(
-        "paraphrase: " + text,
-        return_tensors="pt",
-        padding="longest",
-        truncation=True,
-        max_length=256,
-    ).input_ids
-
-    outputs = model.generate(
-        input_ids,
+        return "Please enter some text to paraphrase."
+    
+    # Preprocess input
+    input_text = "paraphrase: " + text + " </s>"
+    encoding = tokenizer.encode_plus(input_text, max_length=256, padding="max_length", return_tensors="pt", truncation=True)
+    
+    # Generate paraphrased output
+    generated_ids = model.generate(
+        input_ids=encoding["input_ids"],
+        attention_mask=encoding["attention_mask"],
         max_length=256,
-        num_return_sequences=1,
         num_beams=5,
-        temperature=1.5,
+        num_return_sequences=1,
+        no_repeat_ngram_size=2,
+        early_stopping=True
     )
 
-    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+    paraphrased_text = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
+    return paraphrased_text
 
+# Gradio Interface
 iface = gr.Interface(
-    fn=paraphrase,
-    inputs=gr.Textbox(lines=4, label="Enter Text to Paraphrase"),
+    fn=paraphrase_text,
+    inputs=gr.Textbox(lines=6, placeholder="Enter your text here...", label="Original Text"),
     outputs=gr.Textbox(label="Paraphrased Text"),
-    title="Paraphraser Tool",
-    allow_flagging="never",
+    title="AI Paraphraser",
+    description="An advanced paraphrasing tool using the T5 transformer model."
 )
 
 iface.launch()