Create app.py

app.py

@@ -0,0 +1,39 @@
+import gradio as gr
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+# Load the model and tokenizer
+model_name = "SnypzZz/Llama2-13b-Language-translate"
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Function to handle translation
+def translate_text(text, target_language):
+    # Tokenize the input text
+    inputs = tokenizer.encode(text, return_tensors="pt")
+    
+    # Perform translation
+    outputs = model.generate(inputs)
+    
+    # Decode the translated output
+    translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return translated_text
+
+# Gradio interface
+def gradio_app():
+    # Create a Gradio interface
+    iface = gr.Interface(
+        fn=translate_text, 
+        inputs=[
+            gr.inputs.Textbox(label="Input Text"), 
+            gr.inputs.Dropdown(choices=["fr", "es", "de", "zh"], label="Target Language")  # Modify languages accordingly
+        ],
+        outputs=gr.outputs.Textbox(label="Translated Text"),
+        title="Language Translator",
+        description="A translation app using SnypzZz/Llama2-13b-Language-translate"
+    )
+    
+    # Launch the interface
+    iface.launch()
+
+if __name__ == "__main__":
+    gradio_app()