from auto_gptq import AutoGPTQForCausalLM
from transformers import AutoTokenizer, TextGenerationPipeline, TextStreamer

quantized_model = "casperhansen/mpt-7b-8k-chat-gptq"

print('loading model...')

# load quantized model to the first GPU
tokenizer = AutoTokenizer.from_pretrained(quantized_model, use_fast=True)
model = AutoGPTQForCausalLM.from_quantized(quantized_model, device="cuda:0", trust_remote_code=True)

prompt_format = """<|im_start|>system
A conversation between a user and an LLM-based AI assistant. The assistant gives helpful and honest answers.<|im_end|>
<|im_start|>user
{text}<|im_end|>
<|im_start|>assistant

"""

prompt = prompt_format.format(text="What is the difference between nuclear fusion and fission?")

print('generating...')

# or you can also use pipeline
streamer = TextStreamer(tokenizer, skip_special_tokens=True)
tokens = tokenizer(prompt, return_tensors="pt").to(model.device)
output = model.generate(**tokens, max_length=512, streamer=streamer, eos_token_id=tokenizer.eos_token_id)