Can't construct neither GPT4All not GPT4All_J (models are loaded)
wiinnie-the-pooh opened this issue · 1 comments
wiinnie-the-pooh commented
Running on Windows. Use miniconda.
Corresponding stack trace
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ C:\miniconda3\envs\nomic\Lib\site-packages\transformers\configuration_utils.py:658 in │
│ _get_config_dict │
│ │
│ 655 │ │ │
│ 656 │ │ try: │
│ 657 │ │ │ # Load config dict │
│ ❱ 658 │ │ │ config_dict = cls._dict_from_json_file(resolved_config_file) │
│ 659 │ │ │ config_dict["_commit_hash"] = commit_hash │
│ 660 │ │ except (json.JSONDecodeError, UnicodeDecodeError): │
│ 661 │ │ │ raise EnvironmentError( │
│ │
│ C:\miniconda3\envs\nomic\Lib\site-packages\transformers\configuration_utils.py:745 in │
│ _dict_from_json_file │
│ │
│ 742 │ @classmethod │
│ 743 │ def _dict_from_json_file(cls, json_file: Union[str, os.PathLike]): │
│ 744 │ │ with open(json_file, "r", encoding="utf-8") as reader: │
│ ❱ 745 │ │ │ text = reader.read() │
│ 746 │ │ return json.loads(text) │
│ 747 │ │
│ 748 │ def __eq__(self, other): │
│ in decode:322 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xe0 in position 4: invalid continuation byte
During handling of the above exception, another exception occurred:
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ C:\Users\apo\source\repos\nomic\main.py:11 in <module> │
│ │
│ 8 │
│ 9 from nomic.gpt4all import GPT4AllGPU as GPT4 │
│ 10 # from pygpt4all import GPT4All as GPT4 │
│ ❱ 11 m = GPT4(LLAMA_PATH) │
│ 12 config = {'num_beams': 2, │
│ 13 │ │ 'min_new_tokens': 10, │
│ 14 │ │ 'max_length': 100, │
│ │
│ C:\Users\apo\source\repos\nomic\nomic\gpt4all\gpt4all.py:26 in __init__ │
│ │
│ 23 │ │ self.model_path = llama_path │
│ 24 │ │ self.tokenizer_path = llama_path │
│ 25 │ │ self.lora_path = 'nomic-ai/vicuna-lora-multi-turn_epoch_2' │
│ ❱ 26 │ │ self.model = AutoModelForCausalLM.from_pretrained(self.model_path, │
│ 27 │ │ │ │ │ │ │ │ │ │ │ │ │ │ device_map="auto", │
│ 28 │ │ │ │ │ │ │ │ │ │ │ │ │ │ torch_dtype=torch.float16) │
│ 29 │ │ self.tokenizer = AutoTokenizer.from_pretrained(self.tokenizer_path) │
│ │
│ C:\miniconda3\envs\nomic\Lib\site-packages\transformers\models\auto\auto_factory.py:441 in │
│ from_pretrained │
│ │
│ 438 │ │ │ if kwargs_copy.get("torch_dtype", None) == "auto": │
│ 439 │ │ │ │ _ = kwargs_copy.pop("torch_dtype") │
│ 440 │ │ │ │
│ ❱ 441 │ │ │ config, kwargs = AutoConfig.from_pretrained( │
│ 442 │ │ │ │ pretrained_model_name_or_path, │
│ 443 │ │ │ │ return_unused_kwargs=True, │
│ 444 │ │ │ │ trust_remote_code=trust_remote_code, │
│ │
│ C:\miniconda3\envs\nomic\Lib\site-packages\transformers\models\auto\configuration_auto.py:916 in │
│ from_pretrained │
│ │
│ 913 │ │ kwargs["_from_auto"] = True │
│ 914 │ │ kwargs["name_or_path"] = pretrained_model_name_or_path │
│ 915 │ │ trust_remote_code = kwargs.pop("trust_remote_code", False) │
│ ❱ 916 │ │ config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_n │
│ 917 │ │ if "auto_map" in config_dict and "AutoConfig" in config_dict["auto_map"]: │
│ 918 │ │ │ if not trust_remote_code: │
│ 919 │ │ │ │ raise ValueError( │
│ │
│ C:\miniconda3\envs\nomic\Lib\site-packages\transformers\configuration_utils.py:573 in │
│ get_config_dict │
│ │
│ 570 │ │ """ │
│ 571 │ │ original_kwargs = copy.deepcopy(kwargs) │
│ 572 │ │ # Get config dict associated with the base config file │
│ ❱ 573 │ │ config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwar │
│ 574 │ │ if "_commit_hash" in config_dict: │
│ 575 │ │ │ original_kwargs["_commit_hash"] = config_dict["_commit_hash"] │
│ 576 │
│ │
│ C:\miniconda3\envs\nomic\Lib\site-packages\transformers\configuration_utils.py:661 in │
│ _get_config_dict │
│ │
│ 658 │ │ │ config_dict = cls._dict_from_json_file(resolved_config_file) │
│ 659 │ │ │ config_dict["_commit_hash"] = commit_hash │
│ 660 │ │ except (json.JSONDecodeError, UnicodeDecodeError): │
│ ❱ 661 │ │ │ raise EnvironmentError( │
│ 662 │ │ │ │ f"It looks like the config file at '{resolved_config_file}' is not a val │
│ 663 │ │ │ ) │
│ 664 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
OSError: It looks like the config file at 'C:\Users\apo\Downloads\ggml-gpt4all-j.bin' is not a valid JSON file.g0dEngineer commented
Probably using the wrong calls based on mismatched models.
~So with respect to groovy 1.3 bin try:
from pygpt4all import GPT4All_J
model = GPT4All_J('same path where python code is located/to/ggml-gpt4all-j-v1.3-groovy.bin')
~Or with respect to converted bin try:
from pygpt4all.models.gpt4all import GPT4All
AI_MODEL = GPT4All('same path where python code is located/gpt4all-converted.bin')
https://github.com/nomic-ai/pygpt4all
Both of the above loaded successfully for me on Windows.