| from argparse import Namespace | |
| from transformers import AutoTokenizer | |
| import torch | |
| from model import Model | |
| def load_model(model_path, device="cpu", model="model.bin"): | |
| args = Namespace() | |
| args.model_path = model_path | |
| model = torch.load(model, map_location=torch.device(device)) | |
| tokenizer = AutoTokenizer.from_pretrained(args.model_path) | |
| args.dropout = 0.3 | |
| model["dataset"] = Namespace(**model["dataset"]) | |
| predict_model = Model(args, model["dataset"]) | |
| predict_model.load_state_dict(model["model"]) | |
| predict_model.to(device) | |
| return tokenizer, model, predict_model | |