torch import

app.py

@@ -1,60 +1,61 @@
-from transformers import pipeline
-from datasets import Dataset
-import streamlit as st
-
-# Set the background color and layout with set_page_config
-st.set_page_config(
-    page_title="English to Tawra Translator",
-    page_icon=":repeat:",
-    layout="wide",
-)
-
-# Streamlit app setup
-st.title(":repeat: English to Tawra Translator")
-st.markdown("Welcome to the English to Tawra Translator. :sparkles: Simply enter your text in English, and get the translation in Tawra instantly! :thumbsup:")
-
-# Text input
-if 'text_input' not in st.session_state:
-    st.session_state.text_input = ""
-text_input = st.text_area("Enter English text to translate", height=150, value=st.session_state.text_input)
-
-# Define your model from Hugging Face
-model_directory = "repleeka/eng-taw-nmt"
-
-device = 0 if torch.cuda.is_available() else -1
-translation_pipeline = pipeline(
-    task="translation",
-    model="repleeka/eng-taw-nmt",
-    tokenizer="repleeka/eng-taw-nmt",
-    device=device
-)
-
-# Translate button
-if st.button("Translate", key="translate_button"):
-    if text_input:
-        with st.spinner("Translating... Please wait"):
-            # Prepare data for translation
-            sentences = [text_input]
-            data = Dataset.from_dict({"text": sentences})
-
-            # Apply translation
-            try:
-                results = data.map(lambda x: {"translation": translation_pipeline(x["text"])})
-                result = results[0]["translation"][0]['translation_text']
-                
-                # Capitalize the first letter of the result
-                result = result.capitalize()
-
-                # Display translation result with custom styling
-                st.markdown("#### Translated text:")
-                st.markdown(f'<h2 class="result-text">{result}</2>', unsafe_allow_html=True)
-                # st.markdown(result)
-                
-            except Exception as e:
-                st.error(f"Translation error: {e}")
-    else:
-        st.warning("Please enter text to translate.")
-
-# Clear input button
-if st.button("Clear Input"):
-    st.session_state.text_input = ""
+from transformers import pipeline
+from datasets import Dataset
+import streamlit as st
+import torch
+
+# Set the background color and layout with set_page_config
+st.set_page_config(
+    page_title="English to Tawra Translator",
+    page_icon=":repeat:",
+    layout="wide",
+)
+
+# Streamlit app setup
+st.title(":repeat: English to Tawra Translator")
+st.markdown("Welcome to the English to Tawra Translator. :sparkles: Simply enter your text in English, and get the translation in Tawra instantly! :thumbsup:")
+
+# Text input
+if 'text_input' not in st.session_state:
+    st.session_state.text_input = ""
+text_input = st.text_area("Enter English text to translate", height=150, value=st.session_state.text_input)
+
+# Define your model from Hugging Face
+model_directory = "repleeka/eng-taw-nmt"
+
+device = 0 if torch.cuda.is_available() else -1
+translation_pipeline = pipeline(
+    task="translation",
+    model="repleeka/eng-taw-nmt",
+    tokenizer="repleeka/eng-taw-nmt",
+    device=device
+)
+
+# Translate button
+if st.button("Translate", key="translate_button"):
+    if text_input:
+        with st.spinner("Translating... Please wait"):
+            # Prepare data for translation
+            sentences = [text_input]
+            data = Dataset.from_dict({"text": sentences})
+
+            # Apply translation
+            try:
+                results = data.map(lambda x: {"translation": translation_pipeline(x["text"])})
+                result = results[0]["translation"][0]['translation_text']
+                
+                # Capitalize the first letter of the result
+                result = result.capitalize()
+
+                # Display translation result with custom styling
+                st.markdown("#### Translated text:")
+                st.markdown(f'<h2 class="result-text">{result}</2>', unsafe_allow_html=True)
+                # st.markdown(result)
+                
+            except Exception as e:
+                st.error(f"Translation error: {e}")
+    else:
+        st.warning("Please enter text to translate.")
+
+# Clear input button
+if st.button("Clear Input"):
+    st.session_state.text_input = ""