Initial checkin

app.py

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+import streamlit as st
+from transformers import pipeline, AutoTokenizer
+
+base="Helsinki-NLP/opus-mt-en-zh"
+model="edwinlaw/opus-mt-cantonese-v1"
+tokenizer = AutoTokenizer.from_pretrained(base)
+
+def translate(text, src_lang, tgt_lang):
+    translator = pipeline(
+        "translation",
+        model=model,
+        tokenizer=tokenizer,
+        src_lang=src_lang,
+        tgt_lang=tgt_lang,
+    )
+    translated_text = translator(text)
+    return translated_text
+
+st.title("Translate English into Cantonese:")
+
+prompt = st.text_input('English sentence here')
+
+if prompt:
+    translation = translate(prompt, 'en', 'yue')
+    translated_txt = translation[0]['translation_text']
+
+    st.write(translated_txt)
+
+    with st.expander('Chat History'):
+        st.info(translated_txt)

requirements.txt

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+streamlit
+transformers
+transformers[sentencepiece]
+torch