@@ -39,10 +39,10 @@ pip install --upgrade accelerate torch
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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 FP8Config, AutoModelForCausalLM, AutoTokenizer
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from transformers import FineGrainedFP8Config, AutoModelForCausalLM, AutoTokenizer
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model_name = "meta-llama/Meta-Llama-3-8B"
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quantization_config = FP8Config()
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quantization_config = FineGrainedFP8Config()
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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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