[docs] Increase visibility of torch_dtype="auto" (#35067)
* auto-dtype * feedback
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@@ -33,13 +33,14 @@ pip install --upgrade accelerate fbgemm-gpu torch
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If you are having issues with fbgemm-gpu and torch library, you might need to install the nightly release. You can follow the instruction [here](https://pytorch.org/FBGEMM/fbgemm_gpu-development/InstallationInstructions.html#fbgemm-gpu-install-libraries:~:text=found%20here.-,Install%20the%20FBGEMM_GPU%20Package,-Install%20through%20PyTorch)
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By default, the weights are loaded in full precision (torch.float32) regardless of the actual data type the weights are stored in such as torch.float16. Set `torch_dtype="auto"` to load the weights in the data type defined in a model's `config.json` file to automatically load the most memory-optimal data type.
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```py
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from transformers import FbgemmFp8Config, AutoModelForCausalLM, AutoTokenizer
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model_name = "meta-llama/Meta-Llama-3-8B"
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quantization_config = FbgemmFp8Config()
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quantized_model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", quantization_config=quantization_config)
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quantized_model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto", quantization_config=quantization_config)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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input_text = "What are we having for dinner?"
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