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app.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Sun Feb 25 20:10:26 2024
+
+@author: CSU5KOR
+"""
+
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Jan 23 11:46:16 2024
+
+@author: CSU5KOR
+"""
+
+
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+import streamlit as st
+from torch import cuda
+
+if cuda.is_available():
+    device='cuda'
+else:
+    device='cpu'
+
+@st.cache_resource()
+
+def load_model():
+    model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
+    model.to(device)
+    tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")
+    return model,tokenizer
+
+model,tokenizer=load_model()
+st.title("Chinese to multilingual translation app")
+
+st.write("This app demonstrates translation capabilities of LLM")
+
+
+
+col1,col2 = st.columns(2)
+
+with col1:
+    source_language=st.radio("Select source language",["zh","de"])
+    user_text = st.text_area("Enter text for translation")
+   
+
+with col2:
+   target_language=st.radio("Select traget language",["en","de","bn","hi"])
+   if user_text:
+        tokenizer.src_lang = source_language#"zh"#"hi"
+        encoded_text = tokenizer(user_text, return_tensors="pt").to(device)
+        generated_tokens = model.generate(**encoded_text, forced_bos_token_id=tokenizer.get_lang_id(target_language))
+        m2m_translated=tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
+        st.write(m2m_translated)
+        #st.snow()
+       
+
+
+
+
+

requirements.txt

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+transformers==4.37.2
+torch==2.2.0
+streamlit==1.31.1