from datasets import load_dataset
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel


base_model = AutoModelForCausalLM.from_pretrained(
    'meta-llama/Llama-2-7b-chat-hf',
    trust_remote_code=True,
    device_map="auto",
    torch_dtype=torch.float16,   # optional if you have enough VRAM
)
tokenizer = AutoTokenizer.from_pretrained('meta-llama/Llama-2-7b-chat-hf')

model = PeftModel.from_pretrained(base_model, 'FinGPT/fingpt-forecaster_dow30_llama2-7b_lora')
model = model.eval()


if __name__ == "__app__":
    demo.queue(max_size=20).launch()