Closed
Description
Describe the bug
TypeError: expected str, bytes or os.PathLike object, not dict
With config from the readme
│ /root/anaconda3/envs/zero/lib/python3.10/site-packages/lighteval/models/model_loader.py:150 in │
│ load_model_with_accelerate_or_default │
│ │
│ 147 │ elif isinstance(config, VLLMModelConfig): │
│ 148 │ │ if not is_vllm_available(): │
│ 149 │ │ │ raise ImportError(NO_VLLM_ERROR_MSG) │
│ _ 150 │ │ model = VLLMModel(config=config, env_config=env_config) │
│ 151 │ │ return model │
│ 152 │ else: │
│ 153 │ │ model = TransformersModel(config=config, env_config=env_config)
│ /root/anaconda3/envs/zero/lib/python3.10/site-packages/lighteval/models/vllm/vllm_model.py:116 │
│ in __init__ │
│ │
│ 113 │ │ self.data_parallel_size = int(config.data_parallel_size) │
│ 114 │ │ │
│ 115 │ │ self._add_special_tokens = config.add_special_tokens if config.add_special_token │
│ _ 116 │ │ self._tokenizer = self._create_auto_tokenizer(config, env_config) │
│ 117 │ │ │
│ 118 │ │ self._max_length = int(config.max_model_length) if config.max_model_length is no │
│ 119
│ /root/anaconda3/envs/zero/lib/python3.10/site-packages/lighteval/models/vllm/vllm_model.py:202 │
│ in _create_auto_tokenizer │
│ │
│ 199 │ │ return model │
│ 200 │ │
│ 201 │ def _create_auto_tokenizer(self, config: VLLMModelConfig, env_config: EnvConfig): │
│ _ 202 │ │ tokenizer = get_tokenizer( │
│ 203 │ │ │ config.pretrained, │
│ 204 │ │ │ tokenizer_mode="auto", │
│ 205 │ │ │ trust_remote_code=config.trust_remote_code,
│ /root/anaconda3/envs/zero/lib/python3.10/site-packages/vllm/transformers_utils/tokenizer.py:120 │
│ in get_tokenizer │
│ │
│ 117 │ │ kwargs["truncation_side"] = "left" │
│ 118 │ │
│ 119 │ # Separate model folder from file path for GGUF models │
│ _ 120 │ is_gguf = check_gguf_file(tokenizer_name) │
│ 121 │ if is_gguf: │
│ 122 │ │ kwargs["gguf_file"] = Path(tokenizer_name).name │
│ 123 │ │ tokenizer_name = Path(tokenizer_name).parent
│ /root/anaconda3/envs/zero/lib/python3.10/site-packages/vllm/transformers_utils/utils.py:8 in │
│ check_gguf_file │
│ │
│ 5 │
│ 6 def check_gguf_file(model: Union[str, PathLike]) -> bool: │
│ 7 │ """Check if the file is a GGUF model.""" │
│ _ 8 │ model = Path(model) │
│ 9 │ if not model.is_file(): │
│ 10 │ │ return False │
│ 11 │ elif model.suffix == ".gguf":
TypeError: expected str, bytes or os.PathLike object, not dict
To Reproduce
model: # Model specific parameters
base_params:
model_args: "pretrained=Qwen/Qwen2.5-7B-Instruct,dtype=bfloat16,max_model_length=768,gpu_memory_utilisation=0.7" # Model args that you would pass in the command line
generation: # Generation specific parameters
temperature: 1.0
stop_tokens: null
truncate_prompt: false
Expected behavior
can set custom generation params properly
Version info
0.70