Create app.py

app.py

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+from transformers import pipeline
+import gradio as gr
+
+# Load the translation pipeline using the NLLB-200 model
+pipe = pipeline("translation", model="facebook/nllb-200-3.3B")
+
+# Function to translate text
+def translate_text(text, source_lang, target_lang):
+    # Translate the input text
+    translation = pipe(text, src_lang=source_lang, tgt_lang=target_lang)
+    return translation[0]['translation_text']
+
+# Set up Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Text Translation using NLLB-200 (facebook/nllb-200-3.3B)")
+
+    # Input for user's text
+    text_input = gr.Textbox(label="Enter Text", placeholder="Type the text you want to translate")
+
+    # Input for source language
+    source_lang = gr.Textbox(label="Source Language", placeholder="e.g., 'eng' for English", value="eng")
+
+    # Input for target language
+    target_lang = gr.Textbox(label="Target Language", placeholder="e.g., 'fra' for French", value="fra")
+
+    # Output for displaying the translation
+    output_text = gr.Textbox(label="Translated Text")
+
+    # Button to trigger translation
+    translate_button = gr.Button("Translate")
+
+    # Link button click with translation function
+    translate_button.click(fn=translate_text, inputs=[text_input, source_lang, target_lang], outputs=output_text)
+
+# Launch the Gradio app
+demo.launch()