Create app.py

app.py

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+import streamlit as st
+from transformers import MarianMTModel, MarianTokenizer
+
+# Function to load the translation model
+@st.cache_resource
+def load_model():
+    model_name = "Helsinki-NLP/opus-mt-any-to-en"
+    model = MarianMTModel.from_pretrained(model_name)
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    return model, tokenizer
+
+# Translate the text to English
+def translate_to_english(text, model, tokenizer):
+    inputs = tokenizer.encode(text, return_tensors="pt", padding=True)
+    translated = model.generate(inputs, max_length=512)
+    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
+    return translated_text
+
+# Streamlit UI setup
+st.title("Language Translator to English")
+st.write("Translate any language to English using Hugging Face models!")
+
+# Text input field
+input_text = st.text_area("Enter text in any language", "")
+
+if input_text:
+    model, tokenizer = load_model()
+    translated_text = translate_to_english(input_text, model, tokenizer)
+    st.subheader("Translated Text:")
+    st.write(translated_text)