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import torch
from config.model_config import ModelConfig
from src.data.tokenizer import CharacterTokenizer
from src.utils.helpers import generate, setup_logging
def main():
# Setup logging
logger = setup_logging()
# Load config
config = ModelConfig()
# Setup device
device = "cuda" if torch.cuda.is_available() else "cpu"
logger.info(f"Using device: {device}")
# Load tokenizer
with open(config.data_path) as f:
text = f.read()
tokenizer = CharacterTokenizer(text)
# Load trained model
try:
model = torch.load(config.checkpoint_path, map_location=device)
model.eval()
except Exception as e:
logger.error(f"Error loading model: {e}")
return
# Generate text from prompts
while True:
try:
prompt = input("\nEnter a prompt (or 'quit' to exit): ")
if prompt.lower() == "quit":
break
max_tokens = 200
logger.info("\nGenerating...")
result = generate(model, tokenizer, prompt, max_tokens, device)
logger.info("\nGenerated text:")
logger.info("=" * 50)
logger.info(prompt + result)
logger.info("=" * 50)
except KeyboardInterrupt:
logger.info("\nExiting...")
break
except Exception as e:
logger.error(f"Error during generation: {e}")
continue
if __name__ == "__main__":
main()
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