Repository: EleutherAI/lm-evaluation-harness
Issue: TypeError: Value.__init__() missing 1 required positional argument: 'dtype'
Root cause: External Dependency Breakage

I am using **lm-evaluation-harness** to evaluate the `Qwen3-1.7B` model. The task is `ifeval`. However, the following error appears.

~~~bash
# ./run.sh 
2025-09-04:11:04:01 INFO     [__main__:446] Selected Tasks: ['ifeval']
2025-09-04:11:04:01 INFO     [evaluator:202] Setting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234 | Setting fewshot manual seed to 1234
2025-09-04:11:04:01 INFO     [evaluator:240] Initializing hf model, with arguments: {'pretrained': 'models/Qwen3-1.7B', 'dtype': 'auto'}
2025-09-04:11:04:01 WARNING  [accelerate.utils.other:512] Detected kernel version 4.18.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
2025-09-04:11:04:01 INFO     [models.huggingface:147] Using device 'cuda:2'
2025-09-04:11:04:01 INFO     [models.huggingface:414] Model parallel was set to False, max memory was not set, and device map was set to {'': 'cuda:2'}
`torch_dtype` is deprecated! Use `dtype` instead!
Loading checkpoint shards: 100%|██████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00,  2.05it/s]
[nltk_data] Error loading punkt_tab: <urlopen error [Errno 110]
[nltk_data]     Connection timed out>
Downloaded punkt_tab on rank 0
Traceback (most recent call last):
  File "/usr/local/bin/lm_eval", line 8, in <module>
    sys.exit(cli_evaluate())
             ^^^^^^^^^^^^^^
  File "/workspace/lm/lm-evaluation-harness-main/lm_eval/__main__.py", line 455, in cli_evaluate
    results = evaluator.simple_evaluate(
              ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/lm/lm-evaluation-harness-main/lm_eval/utils.py", line 456, in _wrapper
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/workspace/lm/lm-evaluation-harness-main/lm_eval/evaluator.py", line 283, in simple_evaluate
    task_dict = get_task_dict(
                ^^^^^^^^^^^^^^
  File "/workspace/lm/lm-evaluation-harness-main/lm_eval/tasks/__init__.py", line 635, in get_task_dict
    task_name_from_string_dict = task_manager.load_task_or_group(
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/lm/lm-evaluation-harness-main/lm_eval/tasks/__init__.py", line 426, in load_task_or_group
    collections.ChainMap(
  File "/workspace/lm/lm-evaluation-harness-main/lm_eval/tasks/__init__.py", line 428, in <lambda>
    lambda task: self._load_individual_task_or_group(task),
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/lm/lm-evaluation-harness-main/lm_eval/tasks/__init__.py", line 326, in _load_individual_task_or_group
    return _load_task(task_config, task=name_or_config)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/lm/lm-evaluation-harness-main/lm_eval/tasks/__init__.py", line 286, in _load_task
    task_object = ConfigurableTask(config=config)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/lm/lm-evaluation-harness-main/lm_eval/api/task.py", line 865, in __init__
    self.download(self.config.dataset_kwargs)
  File "/workspace/lm/lm-evaluation-harness-main/lm_eval/api/task.py", line 997, in download
    self.dataset = datasets.load_dataset(
                   ^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/datasets/load.py", line 2062, in load_dataset
    builder_instance = load_dataset_builder(
                       ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/datasets/load.py", line 1782, in load_dataset_builder
    dataset_module = dataset_module_factory(
                     ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/datasets/load.py", line 1519, in dataset_module_factory
    ).get_module()
      ^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/datasets/load.py", line 861, in get_module
    config_name: DatasetInfo.from_dict(dataset_info_dict)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/datasets/info.py", line 284, in from_dict
    return cls(**{k: v for k, v in dataset_info_dict.items() if k in field_names})
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "<string>", line 20, in __init__
  File "/usr/local/lib/python3.12/dist-packages/datasets/info.py", line 170, in __post_init__
    self.features = Features.from_dict(self.features)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/datasets/features/features.py", line 1888, in from_dict
    obj = generate_from_dict(dic)
          ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/datasets/features/features.py", line 1468, in generate_from_dict
    return {key: generate_from_dict(value) for key, value in obj.items()}
                 ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/datasets/features/features.py", line 1484, in generate_from_dict
    return class_type(**{k: v for k, v in obj.items() if k in field_names})
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: Value.__init__() missing 1 required positional argument: 'dtype'
~~~


`run.sh`:
~~~bash
#!/bin/bash

lm_eval --model hf \
    --model_args pretrained=models/Qwen3-1.7B,dtype="auto" \
    --tasks ifeval \
    --device cuda:2 \
    --batch_size auto:4
~~~

python version: `3.12.3`
pytorch version: `2.6.0+cu124`