Application: Question & Answering ML Task: MobileBERT Framework: Tensorflow 1.15 Training Information: Quality: 89.84 F1 Precision: FP32 Is Quantized: No Is ONNX: No Dataset: SQUAD v1.1Please refer to README.txt for details on the model training
SSD-MobileNet-v1 models used in MLPerf Inference: A TensorFlow model archived from the TensorFlow...
MobileNet models for TensorFlow archived from github.com/tensorflow/models/blob/master/research/slim...
As deep learning has been adopted in various domains, the inference process is of growing importance...
Please read the readme.txt in the zip file for more information. There is no accuracy validation do...
Application: Question & Answering ML Task: MobileBERT Framework: TensorFlow (Lite) 2.2 Training I...
Application: Semantic Segmentation ML Task: DeepLabV3Plus Framework: TensorFlow 1.15 for training/...
Application: Question & Answering ML Task: MobileBERT Framework: ONNX Training information: sourc...
Application: Image Classification ML Task: MobileNetEdge Framework: Tensorflow Training Information:...
Application: Image Classification ML Task: mobilenetv1 Framework: ONNX (via tensorflow) Training ...
Application: Semantic Segmentation ML Task: DeepLabV3Plus Framework: TensorFlow/TensorFlow Lite Trai...
Application: Image Classification ML Task: MobileNetEdge Framework: Tensorflow-lite Training Informa...
Application: Object Detection ML Task: ResNet-34-SSD Framework: tensorflow 1.9 Training Informati...
BERT TensorFlow model trained on SQuAD v1.1 for MLPerf Inference. To re-create the model, train on S...
Application: Image Classification ML Task: ResNet-50 Framework: ONNX (via tensorflow) Training In...
Application: Object Detection ML Task: ssd-resnet34 Framework: tensorflow 1.12 Training Informat...
SSD-MobileNet-v1 models used in MLPerf Inference: A TensorFlow model archived from the TensorFlow...
MobileNet models for TensorFlow archived from github.com/tensorflow/models/blob/master/research/slim...
As deep learning has been adopted in various domains, the inference process is of growing importance...
Please read the readme.txt in the zip file for more information. There is no accuracy validation do...
Application: Question & Answering ML Task: MobileBERT Framework: TensorFlow (Lite) 2.2 Training I...
Application: Semantic Segmentation ML Task: DeepLabV3Plus Framework: TensorFlow 1.15 for training/...
Application: Question & Answering ML Task: MobileBERT Framework: ONNX Training information: sourc...
Application: Image Classification ML Task: MobileNetEdge Framework: Tensorflow Training Information:...
Application: Image Classification ML Task: mobilenetv1 Framework: ONNX (via tensorflow) Training ...
Application: Semantic Segmentation ML Task: DeepLabV3Plus Framework: TensorFlow/TensorFlow Lite Trai...
Application: Image Classification ML Task: MobileNetEdge Framework: Tensorflow-lite Training Informa...
Application: Object Detection ML Task: ResNet-34-SSD Framework: tensorflow 1.9 Training Informati...
BERT TensorFlow model trained on SQuAD v1.1 for MLPerf Inference. To re-create the model, train on S...
Application: Image Classification ML Task: ResNet-50 Framework: ONNX (via tensorflow) Training In...
Application: Object Detection ML Task: ssd-resnet34 Framework: tensorflow 1.12 Training Informat...
SSD-MobileNet-v1 models used in MLPerf Inference: A TensorFlow model archived from the TensorFlow...
MobileNet models for TensorFlow archived from github.com/tensorflow/models/blob/master/research/slim...
As deep learning has been adopted in various domains, the inference process is of growing importance...
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