from transformers import AutoTokenizer, AutoModelForCausalLM

def generate_text(prompt, language):
try:
# Load the multilingual tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("bert-base-multilingual-cased")
model = AutoModelForCausalLM.from_pretrained("bert-base-multilingual-cased")

    # Generate text
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(**inputs, max_new_tokens=100)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)
except Exception as e:
    print(f"Error generating text: {e}")

Define prompts in different languages

prompts = {
"Hebrew": "מהו הנגזרת של x^2?",
"Arabic": "ما هو المشتق من x^2؟",
"English": "What is the derivative of x^2?"
}

Generate text for each prompt

for language, prompt in prompts.items():
print(f"Language: {language}")
print(f"Prompt: {prompt}")
print(f"Response: {generate_text(prompt, language)}")
print()