Pipeline failure fixes

Author: Aishwarya-Tonpe

superbench/benchmarks/micro_benchmarks/huggingface_model_loader.py

@@ -247,7 +247,7 @@ def _get_model_size(self, model: PreTrainedModel) -> float:
         Returns:
             Number of parameters in millions.
         """
-        return sum(p.numel() for p in model.parameters()) / 1_000_000
+        return float(sum(p.numel() for p in model.parameters())) / 1_000_000
 
     @staticmethod
     def estimate_param_count_from_config(hf_config) -> Optional[int]:

tests/benchmarks/micro_benchmarks/test_huggingface_e2e.py

@@ -4,7 +4,9 @@
 """End-to-end integration tests for HuggingFace model loading.
 
 These tests actually download and load models from HuggingFace Hub.
-Skipped when SB_TEST_CUDA=0.
+The test class is skipped according to ``@decorator.cuda_test``, and
+``test_load_model_to_gpu`` is additionally skipped when
+``torch.cuda.is_available()`` is false.
 """
 
 import pytest