import os
import torch
from flagai.auto_model.auto_loader import AutoLoader
from flagai.model.predictor.predictor import Predictor
from flagai.data.tokenizer import Tokenizer
import bminf
state_dict = "./checkpoints_in/"
model_name = 'aquila-7b'
loader = AutoLoader("lm",
model_dir=state_dict,
model_name=model_name,
device='cuda',
use_cache=True,
fp16=True)
model = loader.get_model()
tokenizer = loader.get_tokenizer()
model.eval()
model.cuda()
predictor = Predictor(model, tokenizer)
texts = [
"汽车EDR是什么",
]
for text in texts:
print('-' * 80)
text = f'{text}'
print(f"text is {text}")
with torch.no_grad():
out = predictor.predict_generate_randomsample(text,
out_max_length=200,
top_p=0.95)
print(f"pred is {out}")