Spaces:
Running
Running
File size: 1,282 Bytes
7aac0a3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 |
import streamlit as st
from transformers import MarianMTModel, MarianTokenizer
st.set_page_config(page_title="English โ Urdu Translator", layout="centered")
st.title("๐ English โ ุงุฑุฏู Translator")
# Language options
direction = st.selectbox("Select Translation Direction", ["English to Urdu", "Urdu to English"])
# Input text
text = st.text_area("Enter Text")
# Load models and tokenizers only once using caching
@st.cache_resource
def load_model_and_tokenizer(src_lang):
if src_lang == "en":
model_name = "Helsinki-NLP/opus-mt-en-ur"
else:
model_name = "Helsinki-NLP/opus-mt-ur-en"
tokenizer = MarianTokenizer.from_pretrained(model_name)
model = MarianMTModel.from_pretrained(model_name)
return tokenizer, model
# Translate
if st.button("Translate"):
if not text.strip():
st.warning("Please enter some text.")
else:
src_lang = "en" if direction == "English to Urdu" else "ur"
tokenizer, model = load_model_and_tokenizer(src_lang)
inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
translated = model.generate(**inputs)
result = tokenizer.decode(translated[0], skip_special_tokens=True)
st.success("Translation:")
st.write(result)
|