Create app.py

app.py

@@ -0,0 +1,37 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+@st.cache(allow_output_mutation=True)
+def load_model():
+
+    checkpoint = "CohereForAI/aya-101"
+    tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+    model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)
+
+    return tokenizer, model
+
+tokenizer, model = load_model()
+
+st.title("Neural Machine Translation")
+
+text = st.text_input("Enter text to translate:")
+src_language = "auto" 
+tgt_language = st.selectbox("Translate to:", ["English", "Hindi", "Turkish"])
+
+if st.button("Translate"):
+    
+    text_input_ids = tokenizer.encode(text, return_tensors="pt")
+
+    if tgt_language == "English":
+        tgt_language = "en" 
+    elif tgt_language == "Hindi":
+        tgt_language = "hi"
+    elif tgt_language == "Turkish":
+        tgt_language = "tr"
+
+    output_ids = model.generate(text_input_ids, 
+                            forced_bos_token_id=tokenizer.lang_code_to_id[tgt_language])  
+    translated_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+
+    st.write(f"Translated text in {tgt_language}:")
+    st.write(translated_text)