ERROR:mteb.evaluation.MTEB:Error while evaluating ImageNet10Clustering: Unsupported number of image dimension
s: 2                                                                                                         
Traceback (most recent call last):
  File "/data/niklas/mieb/mteb/scripts/run_mieb.py", line 83, in <module>          
    results = evaluation.run(model, output_folder="/data/niklas/mieb/results-mieb-final", batch_size=1)      
  File "/data/niklas/mieb/mteb/mteb/evaluation/MTEB.py", line 464, in run                                  
    raise e                                                                                                  
  File "/data/niklas/mieb/mteb/mteb/evaluation/MTEB.py", line 425, in run                                    
    results, tick, tock = self._run_eval(         
  File "/data/niklas/mieb/mteb/mteb/evaluation/MTEB.py", line 300, in _run_eval              
    results = task.evaluate(                                                                                 
  File "/data/niklas/mieb/mteb/mteb/abstasks/AbsTask.py", line 126, in evaluate                              
    scores[hf_subset] = self._evaluate_subset(                                                               
  File "/data/niklas/mieb/mteb/mteb/abstasks/Image/AbsTaskImageClustering.py", line 54, in _evaluate_subset  
    metrics = evaluator(model, encode_kwargs=encode_kwargs)                                                  
  File "/data/niklas/mieb/mteb/mteb/evaluation/evaluators/Image/ClusteringEvaluator.py", line 41, in __call__
    image_embeddings = model.get_image_embeddings(   
  File "/data/niklas/mieb/mteb/mteb/models/align_models.py", line 60, in get_image_embeddings                
    inputs = self.processor(                                                                                 
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/models/align/processing_align.py", 
line 126, in __call__                                                                                        
    image_features = self.image_processor(images, **output_kwargs["images_kwargs"])
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/image_processing_utils.py", line 41
, in __call__                                                                                                
    return self.preprocess(images, **kwargs)
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/utils/generic.py", line 852, in wra
pper                                                  
    return func(*args, **valid_kwargs)                                                                       
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/models/efficientnet/image_processin
g_efficientnet.py", line 328, in preprocess                                                                  
    input_data_format = infer_channel_dimension_format(images[0])
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/image_utils.py", line 243, in infer
_channel_dimension_format
    raise ValueError(f"Unsupported number of image dimensions: {image.ndim}")
ValueError: Unsupported number of image dimensions: 2