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from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
# Load the pre-trained model
MODEL_NAME = "bigcode/starcoder"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, 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")
output = model.generate(**inputs, max_new_tokens=max_tokens)
return tokenizer.decode(output[0], skip_special_tokens=True)
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