| from typing import Any, Dict | |
| from transformers import AutoTokenizer, AutoModel | |
| import torch | |
| class EndpointHandler: | |
| def __init__(self, model_dir: str, **kwargs: Any) -> None: | |
| self.model = AutoModel.from_pretrained( | |
| model_dir, | |
| torch_dtype=torch.bfloat16, | |
| low_cpu_mem_usage=True, | |
| use_flash_attn=False, | |
| trust_remote_code=True, | |
| device_map="auto", | |
| ).eval() | |
| self.tokenizer = AutoTokenizer.from_pretrained( | |
| model_dir, trust_remote_code=True, use_fast=False | |
| ) | |
| def __call__(self, data: Dict[str, Any]) -> Any: | |
| logger.info(f"Received incoming request with {data=}") | |
| if __name__ == "__main__": | |
| handler = EndpointHandler(model_dir="GSAI-ML/LLaDA-8B-Instruct") | |
| print(handler) | |