updated model.py

model.py

@@ -1,16 +1,25 @@
+import os
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
 
-# Load the pre-trained model
-MODEL_NAME = "starcoder"
-tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
-model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, device_map="auto")
+# Correct model name
+MODEL_NAME = "bigcode/starcoder"
+
+# Ensure the token is provided
+HF_TOKEN = os.getenv("HUGGINGFACE_TOKEN")
+if not HF_TOKEN:
+    raise ValueError("Missing Hugging Face token. Set HUGGINGFACE_TOKEN as an environment variable.")
+
+# Load tokenizer and model with authentication
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, token=HF_TOKEN)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, token=HF_TOKEN, device_map="auto")
 
 def generate_code(prompt: str, max_tokens: int = 256):
     """Generates code based on the input prompt."""
     if not prompt.strip():
         return "Error: Empty prompt provided."
 
-    inputs = tokenizer(prompt, return_tensors="pt").to("cuda" if torch.cuda.is_available() else "cpu")
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    inputs = tokenizer(prompt, return_tensors="pt").to(device)
     output = model.generate(**inputs, max_new_tokens=max_tokens)
     return tokenizer.decode(output[0], skip_special_tokens=True)