BitsandbytesQuantization4bits Configuration

Bits and bytes quantization 4 bits parameters.

Parameters

Name	Type	Required	Description
load_in_8bits	boolean	❌	Whether to load the model in 8 bits(LLM.int8() algorithm), default is False. Defaults：False
load_in_4bits	boolean	❌	Whether to load the model in 4 bits. Defaults：True
bnb_4bit_compute_dtype	string	❌	To speedup computation, you can change the data type from float32 (the default value) to bfloat16 Valid values:bfloat16, float16, float32
bnb_4bit_quant_type	string	❌	Quantization datatypes, `fp4` (four bit float) and `nf4` (normal four bit float), only valid when load_4bit=True Valid values:nf4, fp4 Defaults：nf4
bnb_4bit_use_double_quant	boolean	❌	Nested quantization is a technique that can save additional memory at no additional performance cost. This feature performs a second quantization of the already quantized weights to save an additional 0.4 bits/parameter. Defaults：True