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app.py

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+import gradio as gr
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
+
+model_name = "mrm8488/t5-base-finetuned-common_gen"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)  # 🛠️ Force slow tokenizer
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+pipe = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
+
+def enhance(text):
+    prompt = f"paraphrase: {text}"
+    result = pipe(prompt, max_length=128, num_return_sequences=1, do_sample=True)[0]['generated_text']
+    return result
+
+gr.Interface(fn=enhance, inputs="text", outputs="text", title="AI Text Enhancer").launch()

requirements.txt

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+transformers
+torch
+gradio