Docs / Quantization: Replace all occurences of load_in_8bit with bnb config (#31136)
Replace all occurences of `load_in_8bit` with bnb config
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@@ -88,10 +88,10 @@ Check out the [API documentation](#transformers.integrations.PeftAdapterMixin) s
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The `bitsandbytes` integration supports 8bit and 4bit precision data types, which are useful for loading large models because it saves memory (see the `bitsandbytes` integration [guide](./quantization#bitsandbytes-integration) to learn more). Add the `load_in_8bit` or `load_in_4bit` parameters to [`~PreTrainedModel.from_pretrained`] and set `device_map="auto"` to effectively distribute the model to your hardware:
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```py
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
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peft_model_id = "ybelkada/opt-350m-lora"
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model = AutoModelForCausalLM.from_pretrained(peft_model_id, device_map="auto", load_in_8bit=True)
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model = AutoModelForCausalLM.from_pretrained(peft_model_id, quantization_config=BitsAndBytesConfig(load_in_8bit=True))
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```
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## Add a new adapter
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