File size: 1,103 Bytes
ea3d866 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | import sys
from transformers import AutoTokenizer, AutoModelForCausalLM
def generate_text(prompt, model_name="models/iraqi_proverb_model", max_length=50):
# Load the trained model and tokenizer
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
# Encode the prompt and generate text
inputs = tokenizer.encode(prompt, return_tensors="pt")
outputs = model.generate(
inputs,
max_length=max_length,
num_return_sequences=1,
do_sample=True,
top_k=50,
pad_token_id=tokenizer.eos_token_id # Set pad_token_id to eos_token_id to avoid warnings
)
# Decode the output and print the generated text
generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
return generated_text
# Main script
if __name__ == "__main__":
# Get prompt from command-line arguments, default to an example prompt if none provided
prompt = sys.argv[1] if len(sys.argv) > 1 else "في العراق، يقولون"
print("Generated text:", generate_text(prompt))
|