ValueError: Couldn't instantiate the backend tokenizer from one of: (1) a tokenizers library serialization file, (2) a slow tokenizer instance to convert or (3) an equivalent slow tokenizer class to instantiate and convert. You need to have sentencepiece installed to convert a slow tokenizer to a fast one.

[jameeldark2012]

Hi, I was trying to launch the server for the first time "api_inference_server.py" and I got this error :

Detecting GPU...
Initilizing model....
Loading language model...
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ D:\Python\AIwaifu\./api_inference_server.py:35 in <module>                                       │
│                                                                                                  │
│    32                                                                                            │
│    33 print("Initilizing model....")                                                             │
│    34 print("Loading language model...")                                                         │
│ ❱  35 tokenizer = AutoTokenizer.from_pretrained("PygmalionAI/pygmalion-1.3b", use_fast=True)     │
│    36 config = AutoConfig.from_pretrained("PygmalionAI/pygmalion-1.3b", is_decoder=True)         │
│    37 model = AutoModelForCausalLM.from_pretrained("PygmalionAI/pygmalion-1.3b", config=config   │
│    38                                                                                            │
│                                                                                                  │
│ D:\Python\test\.venv\lib\site-packages\transformers\models\auto\tokenization_auto.py:679 in      │
│ from_pretrained                                                                                  │
│                                                                                                  │
│   676 │   │   │   │   raise ValueError(                                                          │
│   677 │   │   │   │   │   f"Tokenizer class {tokenizer_class_candidate} does not exist or is n   │
│   678 │   │   │   │   )                                                                          │
│ ❱ 679 │   │   │   return tokenizer_class.from_pretrained(pretrained_model_name_or_path, *input   │
│   680 │   │                                                                                      │
│   681 │   │   # Otherwise we have to be creative.                                                │
│   682 │   │   # if model is an encoder decoder, the encoder tokenizer class is used by default   │
│                                                                                                  │
│ D:\Python\test\.venv\lib\site-packages\transformers\tokenization_utils_base.py:1804 in           │
│ from_pretrained                                                                                  │
│                                                                                                  │
│   1801 │   │   │   else:                                                                         │
│   1802 │   │   │   │   logger.info(f"loading file {file_path} from cache at {resolved_vocab_fil  │
│   1803 │   │                                                                                     │
│ ❱ 1804 │   │   return cls._from_pretrained(                                                      │
│   1805 │   │   │   resolved_vocab_files,                                                         │
│   1806 │   │   │   pretrained_model_name_or_path,                                                │
│   1807 │   │   │   init_configuration,                                                           │
│                                                                                                  │
│ D:\Python\test\.venv\lib\site-packages\transformers\tokenization_utils_base.py:1958 in           │
│ _from_pretrained                                                                                 │
│                                                                                                  │
│   1955 │   │                                                                                     │
│   1956 │   │   # Instantiate tokenizer.                                                          │
│   1957 │   │   try:                                                                              │
│ ❱ 1958 │   │   │   tokenizer = cls(*init_inputs, **init_kwargs)                                  │
│   1959 │   │   except OSError:                                                                   │
│   1960 │   │   │   raise OSError(                                                                │
│   1961 │   │   │   │   "Unable to load vocabulary from file. "                                   │
│                                                                                                  │
│ D:\Python\test\.venv\lib\site-packages\transformers\models\gpt_neox\tokenization_gpt_neox_fast.p │
│ y:111 in __init__                                                                                │
│                                                                                                  │
│   108 │   │   add_prefix_space=False,                                                            │
│   109 │   │   **kwargs,                                                                          │
│   110 │   ):                                                                                     │
│ ❱ 111 │   │   super().__init__(                                                                  │
│   112 │   │   │   vocab_file,                                                                    │
│   113 │   │   │   merges_file,                                                                   │
│   114 │   │   │   tokenizer_file=tokenizer_file,                                                 │
│                                                                                                  │
│ D:\Python\test\.venv\lib\site-packages\transformers\tokenization_utils_fast.py:120 in __init__   │
│                                                                                                  │
│   117 │   │   │   slow_tokenizer = self.slow_tokenizer_class(*args, **kwargs)                    │
│   118 │   │   │   fast_tokenizer = convert_slow_tokenizer(slow_tokenizer)                        │
│   119 │   │   else:                                                                              │
│ ❱ 120 │   │   │   raise ValueError(                                                              │
│   121 │   │   │   │   "Couldn't instantiate the backend tokenizer from one of: \n"               │
│   122 │   │   │   │   "(1) a `tokenizers` library serialization file, \n"                        │
│   123 │   │   │   │   "(2) a slow tokenizer instance to convert or \n"                           │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ValueError: Couldn't instantiate the backend tokenizer from one of:
(1) a `tokenizers` library serialization file,
(2) a slow tokenizer instance to convert or
(3) an equivalent slow tokenizer class to instantiate and convert.
You need to have sentencepiece installed to convert a slow tokenizer to a fast one.

[HRNPH]

ValueError: Couldn't instantiate the backend tokenizer from one of:
(1) a `tokenizers` library serialization file,
(2) a slow tokenizer instance to convert or
(3) an equivalent slow tokenizer class to instantiate and convert.
You need to have sentencepiece installed to convert a slow tokenizer to a fast one.

This is due to the wrong configuration of mine that didn't include sentencepice in a requirements.txt
You need to have sentencepiece installed to convert a slow tokenizer to a fast one.
you can solve this really fast by

pip install  sentencepiece

inside the terminal, if this still doesn't solve the issue please notice me!

[jameeldark2012]

Server and client started successfully, thanks.