Update app.py

app.py

@@ -1,34 +1,35 @@
 import gradio as gr
 import torch
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
-# Load the grammar correction model
-model_name = "microsoft/deberta-v3-base"
+# Load the GPT model and tokenizer
+model_name = "openai-community/openai-gpt"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
-# Disable fast tokenization by setting `use_fast=False`
-tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
-
-# Function to correct grammar
+# Function for grammar correction using GPT
 def correct_grammar(text):
-    # Encode input text
-    inputs = tokenizer.encode(text, return_tensors="pt")
-    
-    # Generate the corrected text
-    with torch.no_grad():
-        outputs = model.generate(inputs, max_length=512, num_beams=5, early_stopping=True)
+    # Prepare the prompt for grammar correction
+    prompt = f"Correct the grammar of the following sentence:\n{text}\nCorrected: "
+
+    # Encode the input text and generate output
+    inputs = tokenizer.encode(prompt, return_tensors="pt")
+    outputs = model.generate(inputs, max_length=512, num_beams=5, early_stopping=True)
 
-    # Decode the corrected text
+    # Decode the generated text and return the corrected sentence
     corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    # Post-process the output to extract the corrected sentence
+    corrected_text = corrected_text.replace(prompt, "").strip()  # Clean up the result
     return corrected_text
 
-# Gradio Interface
+# Gradio interface for the grammar correction app
 interface = gr.Interface(
     fn=correct_grammar,
     inputs="text",
     outputs="text",
-    title="Grammar Correction",
-    description="Enter a sentence or paragraph to receive grammar corrections using DeBERTa."
+    title="Grammar Correction with GPT",
+    description="Enter a sentence or paragraph to receive grammar corrections using the OpenAI GPT model."
 )
 
 if __name__ == "__main__":