Update README.md

Remove GaudiConfig from the usage example because it is not mandatory anymore

README.md

@@ -23,24 +23,23 @@ This enables to specify:
 ## Usage
 
 The model is instantiated the same way as in the Transformers library.
-The only difference is that the Gaudi configuration has to be loaded and provided to the trainer:
+The only difference is that there are a few new training arguments specific to HPUs:
 
 ```
-from optimum.habana import GaudiConfig, GaudiTrainer, GaudiTrainingArguments
+from optimum.habana import GaudiTrainer, GaudiTrainingArguments
 from transformers import AlbertTokenizer, AlbertModel
 
 tokenizer = AlbertTokenizer.from_pretrained("albert-large-v2")
 model = AlbertModel.from_pretrained("albert-large-v2")
-gaudi_config = GaudiConfig.from_pretrained("Habana/albert-large-v2")
 args = GaudiTrainingArguments(
     output_dir="/tmp/output_dir",
     use_habana=True,
     use_lazy_mode=True,
+    gaudi_config_name="Habana/albert-large-v2",
 )
 
 trainer = GaudiTrainer(
     model=model,
-    gaudi_config=gaudi_config,
     args=args,
     tokenizer=tokenizer,
 )