Update app.py

app.py

@@ -10,23 +10,11 @@ client = InferenceClient("vennify/t5-base-grammar-correction")
 #gr.load("models/vennify/t5-base-grammar-correction").launch()
 
 # Load the model and tokenizer
-model_name = "vennify/t5-base-grammar-correction"
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
+#model_name = "vennify/t5-base-grammar-correction"
+#model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+#tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 
-# Define the function to generate corrected text
-def correct_text(text, max_length, num_beams, temperature):
-    inputs = tokenizer.encode(text, return_tensors="pt")
-    outputs = model.generate(
-        inputs,
-        max_length=max_length,
-        num_beams=num_beams,
-        temperature=temperature,
-        early_stopping=True
-    )
-    corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return corrected_text
 
 
 def respond(