必应词典为您提供Quantization-Type的释义,网络释义: 量化方式;量化类型;量化编码类型;
Returns how the embedding contents of this property should be quantized. public int QuantizationType { [Android.Runtime.Register("getQuantizationType", "()I", "", ApiSince=36)] get; } Property Value Int32 Attributes RegisterAttribute Remarks Returns how the embedding contents of this...
In the decoding method of the decoding method corresponding to the quantization error type according to the present invention, wireless video-on-demand (VOD) service using the Internet network,; For the input packet VOL (Video Object Layer) confirming that the start code is present and; If you...
MPSCNNWeightsQuantizationType Enumeration Options that specify the type of quantization used to generate unsigned integer weights. iOS 12.0+iPadOS 12.0+Mac Catalyst 13.0+macOS 10.14+tvOS 12.0+visionOS 1.0+ enumMPSCNNWeightsQuantizationType:UInt32, @uncheckedSendable ...
MetalPerformanceShaders 名前空間の MetalPerformanceShaders.MPSCnnWeightsQuantizationType についての詳細をご確認ください。
String qType = (String)wp.getQuantizationType().getDefault(); float baseStep = ((Float)wp.getQuantizationStep().getDefault()).floatValue(); int gb = ((Integer)wp.getGuardBits().getDefault()).intValue(); 代码示例来源:origin: net.java.dev.jai-imageio/jai-imageio-jpeg2000 ...
1. GGML Quantization Type 2. `static const struct ggml_type_traits type_traits[GGML_TYPE_COUNT]` 3. `Q#_K_M` and `Q#_K` References 什么神仙妖魔,不过是他们禁锢异族命运的枷锁! GGUF https://huggingface.co/docs/hub/gguf docs/hub/gguf.md ...
MPSCNNWeightsQuantizationType Options that specify the type of quantization used to generate unsigned integer weights. iOS 12.0+ iPadOS 12.0+ macOS 10.14+ Mac Catalyst 13.0+ tvOS 12.0+ visionOS 1.0+ enum MPSCNNWeightsQuantizationType : UInt32, @unchecked Sendable Topics Enumeration Cases case none...
"general.file_type":GGMLFileQuantizationType.MOSTLY_Q2_K, "general.name":"LLaMA v2", "general.quantization_version":2, "llama.attention.head_count":32, Expand DownExpand Up@@ -96,7 +98,7 @@ describe("gguf", () => { tensor_count:291n, ...
from onnxruntime.quantization import quantize_dynamic, QuantType import onnx # 加载已导出的ONNX模型 model_path = "matmul_model.onnx" quantized_model_path = "matmul_model_quantized.onnx" # 对模型进行动态量化 quantize_dynamic( model_path, ...