Create app.py

app.py

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+!pip install gradio transformers pandas torch
+
+import gradio as gr
+import pandas as pd
+import torch
+from transformers import MarianMTModel, MarianTokenizer
+
+# Load the fine-tuned MarianMT model and tokenizer
+# Replace with the path to your model directory
+model_dir = '/content/drive/MyDrive/fine_tuned_marian'  # Replace with the correct path
+model = MarianMTModel.from_pretrained(model_dir)
+tokenizer = MarianTokenizer.from_pretrained(model_dir)
+
+# Function to translate text
+def translate_arabic_to_english(arabic_text):
+    # Tokenize the input text
+    inputs = tokenizer(arabic_text, return_tensors="pt", padding=True, truncation=True, max_length=128)
+
+    # Move inputs to the same device as the model
+    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+    model.to(device)
+    inputs = {k: v.to(device) for k, v in inputs.items()}
+
+    # Generate translation
+    with torch.no_grad():
+        translated_ids = model.generate(**inputs)
+
+    # Decode the translated text
+    translated_text = tokenizer.decode(translated_ids[0], skip_special_tokens=True)
+    return translated_text
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=translate_arabic_to_english,
+    inputs=gr.Textbox(lines=5, placeholder="Enter Arabic text here..."),
+    outputs="text",
+    title="Arabic to English Machine Translation",
+    description="Translate Arabic text to English ",
+)
+
+# Launch the interface
+iface.launch()