Create app.py

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_NL2Code")
+model = AutoModelForSeq2SeqLM.from_pretrained("AhmedSSoliman/MarianCG_NL2Code")
+
+def generate_code(NL):
+    inputs = tokenizer([NL], padding="max_length", truncation=True, max_length=512, return_tensors="pt")
+    input_ids = inputs.input_ids.to("cuda")
+    attention_mask = inputs.attention_mask.to("cuda")
+    outputs = new_model.generate(input_ids, attention_mask=attention_mask)
+    # all special tokens including will be removed
+    output_code = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    return output_code
+    
+
+iface = gr.Interface(fn=generate_code, inputs="text", outputs="text")
+iface.launch()
+
+#output_text = gr.outputs.Textbox()
+#gr.Interface(generate_code,"textbox", output_text, title="MarianMT Code Generation", description="MarianMT Code Generation").launch()