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update eval

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jingyaogong 2025-04-09 16:56:57 +08:00
parent 4a758564e4
commit d503093ec4
1 changed files with 3 additions and 3 deletions
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6
eval_model.py
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@ -16,7 +16,7 @@ def init_model(args):
tokenizer = AutoTokenizer.from_pretrained('./model/minimind_tokenizer')
if args.load == 0:
moe_path = '_moe' if args.use_moe else ''
modes = {0: 'pretrain', 1: 'full_sft', 2: 'rlhf', 3: 'reason'}
modes = {0: 'pretrain', 1: 'full_sft', 2: 'rlhf', 3: 'reason', 4: 'grpo'}
ckp = f'./{args.out_dir}/{modes[args.model_mode]}_{args.dim}{moe_path}.pth'
model = MiniMindLM(LMConfig(
@ -123,7 +123,7 @@ def main():
parser.add_argument('--stream', default=True, type=bool)
parser.add_argument('--load', default=0, type=int, help="0: 原生torch权重，1: transformers加载")
parser.add_argument('--model_mode', default=1, type=int,
help="0: 预训练模型，1: SFT-Chat模型，2: RLHF-Chat模型，3: Reason模型")
help="0: 预训练模型，1: SFT-Chat模型，2: RLHF-Chat模型，3: Reason模型，4: RLAIF-Chat模型")
args = parser.parse_args()
model, tokenizer = init_model(args)
@ -143,7 +143,7 @@ def main():
messages,
tokenize=False,
add_generation_prompt=True
)[-args.max_seq_len + 1:] if args.model_mode != 0 else (tokenizer.bos_token + prompt)
)[-args.max_seq_len - 1:] if args.model_mode != 0 else (tokenizer.bos_token + prompt)
answer = new_prompt
with torch.no_grad():