lodhrangpt commited on
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145a35c
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Create app.py

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  1. app.py +51 -0
app.py ADDED
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+ import gradio as gr
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+ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, pipeline
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+
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+ # Load the translation model and tokenizer from Hugging Face
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+ # Here, we use the "Helsinki-NLP" translation models
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+ model_name = "Helsinki-NLP/opus-mt-en-fr" # Example model for English to French
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+ model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
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+ translator = pipeline("translation", model=model, tokenizer=tokenizer)
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+
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+ # Define the translation function
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+ def translate_text(text, target_language):
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+ model_name = f"Helsinki-NLP/opus-mt-en-{target_language}"
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+ translator = pipeline("translation", model=model_name)
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+ translation = translator(text)[0]['translation_text']
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+ return translation
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+
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+ # Set up the Gradio interface
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+ languages = {
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+ "en": "English",
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+ "es": "Spanish",
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+ "fr": "French",
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+ "de": "German",
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+ "zh": "Chinese (Mandarin)",
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+ "ja": "Japanese",
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+ "ko": "Korean",
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+ "it": "Italian",
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+ "pt": "Portuguese",
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+ "ru": "Russian",
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+ "hi": "Hindi",
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+ "ar": "Arabic",
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+ "nl": "Dutch",
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+ "tr": "Turkish",
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+ "el": "Greek",
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+ "ur": "Urdu"
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+ }
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+
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+
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+ iface = gr.Interface(
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+ fn=translate_text,
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+ inputs=[
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+ gr.inputs.Textbox(label="Enter text to translate"),
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+ gr.inputs.Dropdown(list(languages.keys()), label="Target Language", type="value")
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+ ],
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+ outputs="text",
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+ live=True,
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+ title="Text Translator",
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+ description="Translate text into multiple languages using Hugging Face models."
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+ )
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+
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+ iface.launch()