Remove all traces of low_cpu_mem_usage (#38792)

* remove it from all py files

* remove it from the doc

* remove it from examples

* style

* remove traces of _fast_init

* Update test_peft_integration.py

* CIs

tests/models/jamba/test_modeling_jamba.py

@@ -527,7 +527,6 @@ class JambaModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixi
                     tmpdirname,
                     torch_dtype=torch.float16,
                     attn_implementation="flash_attention_2",
-                    low_cpu_mem_usage=True,
                     load_in_4bit=True,
                 )
 
@@ -563,7 +562,10 @@ class JambaModelIntegrationTest(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
         model_id = "ai21labs/Jamba-tiny-dev"
-        cls.model = JambaForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, low_cpu_mem_usage=True)
+        cls.model = JambaForCausalLM.from_pretrained(
+            model_id,
+            torch_dtype=torch.bfloat16,
+        )
         cls.tokenizer = AutoTokenizer.from_pretrained(model_id)
         cls.device_properties = get_device_properties()