Skingpt4 error allocation
(base) PS C:\Users\asus> python demo.py --cfg-path eval_configs/skingpt4_eval_llama2_13bchat.yaml --gpu-id 0Initializing Chattokenizer.json: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 466k/466k [00:00<00:00, 506kB/s]Loading VITLoading VIT DoneLoading Q-FormerLoading Q-Former DoneLoading LLM tokenizerC:\ProgramData\anaconda3\Lib\site-packages\transformers\tokenization_utils_base.py:1930: FutureWarning: Calling LlamaTokenizer.from_pretrained() with the path to a single file or url is deprecated and won’t be possible anymore in v5. Use a model identifier or the path to a directory instead.warnings.warn(You are using the default legacy behaviour of the <class ‘transformers.models.llama.tokenization_llama.LlamaTokenizer’>. This is expected, and simply means that thelegacy(previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, setlegacy=False. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in⚠️⚠️[`T5Tokenize`] Fix T5 family tokenizers⚠️⚠️ by ArthurZucker · Pull Request #24565 · huggingface/transformers · GitHubTraceback (most recent call last):File “C:\Users\asus\demo.py”, line 60, inmodel = model_cls.from_config(model_config).to(‘cuda:{}’.format(args.gpu_id))^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File “C:\Users\asus\skingpt4\models\skin_gpt4.py”, line 245, in from_configmodel = cls(^^^^File “C:\Users\asus\skingpt4\models\skin_gpt4.py”, line 87, ininitself.llm_tokenizer = LlamaTokenizer.from_pretrained(llm_model, use_fast=False)^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File “C:\ProgramData\anaconda3\Lib\site-packages\transformers\tokenization_utils_base.py”, line 2029, in from_pretrainedreturn cls.from_pretrained(^^^^^^^^^^^^^^^^^^^^^File “C:\ProgramData\anaconda3\Lib\site-packages\transformers\tokenization_utils_base.py”, line 2261, infrom_pretrainedtokenizer = cls(*init_inputs, **init_kwargs)^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File “C:\ProgramData\anaconda3\Lib\site-packages\transformers\models\llama\tokenization_llama.py”, line 178, ininitself.sp_model = self.get_spm_processor(kwargs.pop(“from_slow”, False))^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File “C:\ProgramData\anaconda3\Lib\site-packages\transformers\models\llama\tokenization_llama.py”, line 203, in get_spm_processortokenizer.Load(self.vocab_file)File "C:\ProgramData\anaconda3\Lib\site-packages\sentencepiece_init.py", line 905, in Loadreturn self.LoadFromFile(model_file)^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "C:\ProgramData\anaconda3\Lib\site-packages\sentencepiece_init.py", line 310, in LoadFromFilereturn _sentencepiece.SentencePieceProcessor_LoadFromFile(self, arg)^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^RuntimeError: Internal: D:\a\sentencepiece\sentencepiece\src\sentencepiece_processor.cc(1102) [model_proto->ParseFromArray(serialized.data(), serialized.size())]i  have no clue how to solve these error i think i misses the path in the yaml file i checked nothing there