from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

question = "If millionaires have butlers, why don't million dollar language models have a butler too? I think its because "

model_name = "akhauriyash/Llama-3.2-3B-Butler"
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)

generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
response = generator(question, max_new_tokens=200, do_sample=True, top_p=0.95, temperature=0.7)

print(response[0]['generated_text'][len(question):])

def set_sparsity(model, sparsity):
    for module in model.modules():
        if module.__class__.__name__.__contains__("AttentionExperimental"):
            module.token_sparse_method = sparsity
            module.set_token_sparsity()
    return model

model = set_sparsity(model, "fixed_60pc")