This model is fine-tuned based on MLPerf Inference BERT PyTorch Model on SQuAD v1.1 dataset and converted to ONNX using the script in MLPerf inference repo: https://github.com/mlperf/inference The quantization method is: per-tensor, symmetric, zero_point=0. It uses ONNX QuantizeLinear and DequantizeLinear to achieve the quantization. Achieved accuracy is f1_score=90.482%. The description for fine-tuning step is in "MLPerf INT8 BERT Finetuning.pdf"
Application: Single-stage Object Detection Base Model: Retinanet with Resnext50 backbone Framework...
3D-Unet reference models trained on KiTS19 dataset for MLPerf Inference. See MLPerf Inference GitHub...
3D-Unet PyTorch model trained on BraTS 2019 dataset (fold 1) for MLPerf Inference. See MLPerf Infere...
This model is fine-tuned based on MLPerf Inference BERT PyTorch Model on SQuAD v1.1 dataset and conv...
This model is finetuned and quantized based on a pretrained huggingface BERT model. The quantizatio...
This model is converted from the MLPerf Inference BERT Tensorflow Model on SQuAD v1.1 dataset using ...
This model is converted from the MLPerf Inference BERT Tensorflow Model on SQuAD v1.1 dataset using ...
This model is frozen from official MLPerf inference benchmark BERT model at this zenodo link with ba...
Please read the readme.txt in the zip file for more information. There is no accuracy validation do...
BERT Large. { "hidden-size": 1024, "num-attention-heads": 16, "num-layers": 24, "max-seq-length": 3...
Transformer based architectures have become de-facto models used for a range of Natural Language Pro...
Application: Question & Answering ML Task: MobileBERT Framework: ONNX Training information: sourc...
Application: Single-stage Object Detection Base Model: Retinanet with Resnext50 backbone Framework...
This 3D-Unet ONNX model is converted from https://zenodo.org/record/3904106. See MLPerf Inference Gi...
Application: Object Detection ML Task: ssd-resnet34 Framework: onnx Training Information: Quali...
Application: Single-stage Object Detection Base Model: Retinanet with Resnext50 backbone Framework...
3D-Unet reference models trained on KiTS19 dataset for MLPerf Inference. See MLPerf Inference GitHub...
3D-Unet PyTorch model trained on BraTS 2019 dataset (fold 1) for MLPerf Inference. See MLPerf Infere...
This model is fine-tuned based on MLPerf Inference BERT PyTorch Model on SQuAD v1.1 dataset and conv...
This model is finetuned and quantized based on a pretrained huggingface BERT model. The quantizatio...
This model is converted from the MLPerf Inference BERT Tensorflow Model on SQuAD v1.1 dataset using ...
This model is converted from the MLPerf Inference BERT Tensorflow Model on SQuAD v1.1 dataset using ...
This model is frozen from official MLPerf inference benchmark BERT model at this zenodo link with ba...
Please read the readme.txt in the zip file for more information. There is no accuracy validation do...
BERT Large. { "hidden-size": 1024, "num-attention-heads": 16, "num-layers": 24, "max-seq-length": 3...
Transformer based architectures have become de-facto models used for a range of Natural Language Pro...
Application: Question & Answering ML Task: MobileBERT Framework: ONNX Training information: sourc...
Application: Single-stage Object Detection Base Model: Retinanet with Resnext50 backbone Framework...
This 3D-Unet ONNX model is converted from https://zenodo.org/record/3904106. See MLPerf Inference Gi...
Application: Object Detection ML Task: ssd-resnet34 Framework: onnx Training Information: Quali...
Application: Single-stage Object Detection Base Model: Retinanet with Resnext50 backbone Framework...
3D-Unet reference models trained on KiTS19 dataset for MLPerf Inference. See MLPerf Inference GitHub...
3D-Unet PyTorch model trained on BraTS 2019 dataset (fold 1) for MLPerf Inference. See MLPerf Infere...