Upload app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, T5ForConditionalGeneration
+
+# Load the CoEdIT-xl model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("grammarly/coedit-xl")
+model = T5ForConditionalGeneration.from_pretrained("grammarly/coedit-xl")
+
+def edit_text(input_text):
+    # Tokenize input text
+    input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+    # Generate edited text
+    outputs = model.generate(input_ids, max_length=256)
+    edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return edited_text
+
+# Create a Gradio interface
+iface = gr.Interface(
+    fn=edit_text,
+    inputs=gr.Textbox(label="Enter a sentence to edit:"),
+    outputs=gr.Textbox(label="Edited sentence:"),
+    title="CoEdIT Text Editor",
+    description="Edit text using the CoEdIT-xl model.",
+)
+
+if __name__ == "__main__":
+    iface.launch()