test

app.py

@@ -10,6 +10,10 @@ args = TTSettings(num_beams=5, min_length=1)
 tokenizer = T5Tokenizer.from_pretrained("thaboe01/t5-spelling-corrector")
 model = T5ForConditionalGeneration.from_pretrained("thaboe01/t5-spelling-corrector")
 
+# Place the model on the appropriate device
+device = "cuda" if st.session_state.use_gpu else "cpu"  # Use GPU if available, otherwise CPU
+model = model.to(device)
+
 # Function to split text into chunks
 def split_text(text, chunk_size=500):
     chunks = []
@@ -19,9 +23,9 @@ def split_text(text, chunk_size=500):
 
 # Function to correct spelling using T5 model
 def correct_spelling(text):
-    input_ids = tokenizer(text, return_tensors="pt").input_ids
+    input_ids = tokenizer(text, return_tensors="pt").input_ids.to(device)
     outputs = model.generate(input_ids)
-    corrected_text = tokenizer.decode(outputs[0])
+    corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return corrected_text
 
 # Streamlit app