diff --git a/src/lighteval/models/vllm/vllm_model.py b/src/lighteval/models/vllm/vllm_model.py index 3398f7218..d9da629e5 100644 --- a/src/lighteval/models/vllm/vllm_model.py +++ b/src/lighteval/models/vllm/vllm_model.py @@ -37,7 +37,7 @@ GenerativeResponse, LoglikelihoodResponse, ) -from lighteval.models.utils import _get_dtype, _simplify_name +from lighteval.models.utils import _get_dtype, _get_model_sha, _simplify_name from lighteval.tasks.requests import ( GreedyUntilRequest, LoglikelihoodRequest, @@ -100,6 +100,9 @@ def __post_init__(self): if not self.generation_parameters: self.generation_parameters = GenerationParameters() + def get_model_sha(self): + return _get_model_sha(repo_id=self.pretrained, revision=self.revision) + class VLLMModel(LightevalModel): def __init__( @@ -124,10 +127,10 @@ def __init__( self.multichoice_continuations_start_space = config.multichoice_continuations_start_space self.model_name = _simplify_name(config.pretrained) - self.model_sha = "" # config.get_model_sha() + self.model_sha = config.get_model_sha() self.precision = _get_dtype(config.dtype, config=self._config) - self.model_info = ModelInfo(model_name=self.model_name, model_sha=self.model_sha) + self.model_info = ModelInfo(model_name=self.model_name, model_sha=self.model_sha, model_dtype=config.dtype) self.sampling_params = SamplingParams(**config.generation_parameters.to_vllm_openai_dict()) self.pairwise_tokenization = config.pairwise_tokenization @@ -203,7 +206,7 @@ def _create_auto_tokenizer(self, config: VLLMModelConfig, env_config: EnvConfig) config.pretrained, tokenizer_mode="auto", trust_remote_code=config.trust_remote_code, - tokenizer_revision=config.revision, + revision=config.revision + (f"/{config.subfolder}" if config.subfolder is not None else ""), ) tokenizer.pad_token = tokenizer.eos_token return tokenizer