Upload model_utils.py

model/model_utils.py

@@ -0,0 +1,17 @@
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+def load_model():
+    model_name = "Salesforce/codet5-base"
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+    model.eval()
+
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    model.to(device)
+    return tokenizer, model, device
+
+def generate_explanation(prompt, tokenizer, model, device):
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True).to(device)
+    output = model.generate(**inputs, max_new_tokens=256, temperature=0.7)
+    return tokenizer.decode(output[0], skip_special_tokens=True)