Add application file

app.py

@@ -0,0 +1,41 @@
+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import gradio as gr     
+
+def envit5_translation(text):
+    inputs = [f"en: {text}"]
+    outputs = model.generate(tokenizer(inputs, return_tensors="pt", padding=True).input_ids.to(device), max_length=512)
+    results = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    return results[0][4:]
+
+def my_translation(text):
+    return "My Translation"
+
+def finetune_BERT(text):
+    return "BERT"
+
+def translation(text):
+    output1 = my_translation(text)
+    output2 = envit5_translation(text)
+    output3 = finetune_BERT(text)
+
+    return (output1, output2, output3)
+
+if __name__ == "__main__":
+    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+    model_name = "VietAI/envit5-translation"
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_name).to(device)
+
+    inputs = [
+    "textbox"
+    ]
+
+    with gr.Blocks() as app:
+        gr.Interface(
+            fn=translation,
+            inputs=inputs,
+            outputs=["textbox", "textbox", "textbox"]
+            )
+
+    app.launch(shared = True)