Create app.py

app.py

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+import streamlit as st
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+
+# Load the model and tokenizer
+model_name = "facebook/m2m100_418M"
+tokenizer = M2M100Tokenizer.from_pretrained(model_name)
+model = M2M100ForConditionalGeneration.from_pretrained(model_name)
+
+# Streamlit UI
+st.title("English to Multiple Language Translator")
+st.write("Translate English text into different languages using AI.")
+
+# Input text
+input_text = st.text_area("Enter English text:", value="")
+
+# Language selection
+language_options = {
+    "French": "fr",
+    "Spanish": "es",
+    "German": "de",
+    "Chinese": "zh",
+    "Arabic": "ar",
+    "Hindi": "hi",
+    "Japanese": "ja",
+    "Russian": "ru",
+    "Portuguese": "pt",
+    "Italian": "it"
+}
+selected_language = st.selectbox("Select target language:", list(language_options.keys()))
+
+if st.button("Translate"):
+    if input_text:
+        # Set target language
+        target_language = language_options[selected_language]
+        tokenizer.src_lang = "en"
+        encoded_input = tokenizer(input_text, return_tensors="pt")
+
+        # Generate translation
+        generated_tokens = model.generate(**encoded_input, forced_bos_token_id=tokenizer.get_lang_id(target_language))
+        translated_text = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
+
+        # Display translated text
+        st.write(f"**Translated text ({selected_language}):**")
+        st.write(translated_text)
+    else:
+        st.write("Please enter text to translate.")
+