Update caption_refiner.py

caption_refiner.py

@@ -1,4 +1,5 @@
 from transformers import T5Tokenizer, T5ForConditionalGeneration
+import torch
 
 # Load the T5 model and tokenizer
 tokenizer = T5Tokenizer.from_pretrained("t5-base")
@@ -7,10 +8,11 @@ model = T5ForConditionalGeneration.from_pretrained("t5-base")
 def refine_caption(initial_caption):
     # Prepare the input for the T5 model
     input_text = f"refine caption: {initial_caption}"
-    input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+    inputs = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True, max_length=512)
     
     # Generate the refined caption
-    outputs = model.generate(input_ids, max_new_tokens=100, num_return_sequences=1)
+    with torch.no_grad():
+        outputs = model.generate(inputs.input_ids, max_new_tokens=100, num_return_sequences=1)
     
     # Decode the refined caption
     refined_caption = tokenizer.decode(outputs[0], skip_special_tokens=True)