在使用transformers的from_pretrained加载模型时,我们可以选择使用 quantization_config来指定量化方式(如4bit/8bit)。然而当我们指定该参数时,无论是否在该参数中设置4bit或8bit的量化方式,加载的模型都是量化后的模型。 quantization_config = BitsAndBytesConfig(load_in_8
针对你的问题“please, pass a bitsandbytesconfig object in quantization_config argument”,以下是详细的解答: 创建一个BitsAndBytesConfig对象: 在使用bitsandbytes库进行模型量化时,你需要首先创建一个BitsAndBytesConfig对象。这个对象用于配置量化的具体参数,比如量化位数、量化类型等。 python from transformers im...
as supported load-time Recent additions to diffusers addedBitsAndBytesConfigas well asTorchAoConfigoptions that can be used asquantization_configwhen loading model components usingfrom_pretrained for example: quantization_config=BitsAndBytesConfig(...)transformer=SD3Transformer2DModel.from_pretrained(repo_id...
quantization_config={"load_in_4bit": True} ) See:https://huggingface.co/docs/transformers/en/main_classes/quantization#transformers.BitsAndBytesConfigfor all the options. 3. Fix issues that all the vision / audio models cannot use transformers bnb quantization. 4. Remove these old models: 'aq...
"bitsandbytes", "gguf", "modelopt", "w8a8_int8", Member zhyncs Jan 14, 2025 Is w8a8_int8 for int8 and w8a8_fp8 for fp8? Collaborator Author ispobock Jan 14, 2025 Maybe fp8 for w8a8_fp8? Collaborator Author ispobock Jan 14, 2025 I use w8a8_int8 since it's more...