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app.py

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+import torch
+import transformers
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import gradio as gr
+
+tokenizer = AutoTokenizer.from_pretrained("AhmedSSoliman/MarianCG-CoNaLa-Large")
+model = AutoModelForSeq2SeqLM.from_pretrained("AhmedSSoliman/MarianCG-CoNaLa-Large")
+
+def generate_code(NL):
+    inputs = tokenizer(NL, padding="max_length", truncation=True, max_length=512, return_tensors="pt")
+    input_ids = inputs.input_ids
+    attention_mask = inputs.attention_mask
+    outputs = model.generate(input_ids, attention_mask=attention_mask)
+
+    output_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return output_code
+    
+
+iface = gr.Interface(fn=generate_code, inputs="text", outputs="text")
+iface.launch()
+#iface.launch(share=True)
+
+#output_text = gr.outputs.Textbox()
+#gr.Interface(generate_code,"textbox", output_text, title="MarianCG model for Code Generation", description="MarianCG model for Code Generation").launch()