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
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@@ -144,7 +144,7 @@ class Cohere2IntegrationTest(unittest.TestCase):
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]
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model = AutoModelForCausalLM.from_pretrained(
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model_id, low_cpu_mem_usage=True, torch_dtype=torch.bfloat16, attn_implementation="eager"
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model_id, torch_dtype=torch.bfloat16, attn_implementation="eager"
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).to(torch_device)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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@@ -168,7 +168,7 @@ class Cohere2IntegrationTest(unittest.TestCase):
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# fmt: on
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model = AutoModelForCausalLM.from_pretrained(
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model_id, low_cpu_mem_usage=True, torch_dtype=torch.float16, attn_implementation="eager"
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model_id, torch_dtype=torch.float16, attn_implementation="eager"
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).to(torch_device)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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@@ -189,7 +189,7 @@ class Cohere2IntegrationTest(unittest.TestCase):
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]
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model = AutoModelForCausalLM.from_pretrained(
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model_id, low_cpu_mem_usage=True, torch_dtype=torch.bfloat16, attn_implementation="flex_attention"
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model_id, torch_dtype=torch.bfloat16, attn_implementation="flex_attention"
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).to(torch_device)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
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