Create app.py

app.py

@@ -0,0 +1,42 @@
+import streamlit as st
+from transformers import MarianMTModel, MarianTokenizer
+
+# Initialize the model and tokenizer
+def load_model_and_tokenizer(target_lang):
+    model_name = f'Helsinki-NLP/opus-mt-en-{target_lang}'
+    model = MarianMTModel.from_pretrained(model_name)
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    return model, tokenizer
+
+# Function to translate text
+def translate_text(text, model, tokenizer):
+    tokens = tokenizer(text, return_tensors="pt", padding=True)
+    translated_tokens = model.generate(**tokens)
+    translated_text = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
+    return translated_text
+
+# Streamlit app
+st.title("Language Translator")
+
+# Input text
+input_text = st.text_area("Enter text to translate", "Hello, how are you?")
+
+# Language selection
+target_language = st.selectbox(
+    "Select target language",
+    ["fr", "de", "es", "it", "pt", "ru", "zh", "ja", "ar"]
+)
+
+# Load model and tokenizer based on selected language
+if target_language:
+    model, tokenizer = load_model_and_tokenizer(target_language)
+    
+    if st.button("Translate"):
+        if input_text:
+            translated_text = translate_text(input_text, model, tokenizer)
+            st.subheader("Translated text")
+            st.write(translated_text)
+        else:
+            st.error("Please enter some text to translate.")
+
+streamlit run app.py