[Transformers] Drop creation of HF model cards

src/sparseml/transformers/masked_language_modeling.py

@@ -744,11 +744,6 @@ def compute_metrics(eval_preds):
             num_samples_to_export=data_args.num_export_samples
         )
 
-    if training_args.push_to_hub:
-        trainer.push_to_hub(**kwargs)
-    else:
-        trainer.create_model_card(**kwargs)
-
 
 def _mp_fn(index):
     # For xla_spawn (TPUs)

src/sparseml/transformers/question_answering.py

@@ -844,10 +844,6 @@ def compute_metrics(p: EvalPrediction):
         trainer.save_sample_inputs_outputs(
             num_samples_to_export=data_args.num_export_samples
         )
-    if training_args.push_to_hub:
-        trainer.push_to_hub(**kwargs)
-    else:
-        trainer.create_model_card(**kwargs)
 
 
 def _mp_fn(index):

src/sparseml/transformers/text_classification.py

@@ -873,11 +873,6 @@ def compute_metrics(p: EvalPrediction):
             num_samples_to_export=data_args.num_export_samples
         )
 
-    if training_args.push_to_hub:
-        trainer.push_to_hub(**kwargs)
-    else:
-        trainer.create_model_card(**kwargs)
-
 
 def _split_train_val(train_dataset, val_ratio):
     # Fixed random seed to make split consistent across runs with the same ratio

src/sparseml/transformers/token_classification.py

@@ -729,11 +729,6 @@ def compute_metrics(p):
             num_samples_to_export=data_args.num_export_samples
         )
 
-    if training_args.push_to_hub:
-        trainer.push_to_hub(**kwargs)
-    else:
-        trainer.create_model_card(**kwargs)
-
 
 def _mp_fn(index):
     # For xla_spawn (TPUs)