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Remove OnnxRuntime BERT inference notebooks #183

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Merged
prasanthpul merged 8 commits into from
Apr 8, 2020
Merged

Remove OnnxRuntime BERT inference notebooks #183

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ebc2491
update pytorch bert tutorial
tianleiwu Feb 28, 2020
b24b706
update test tool
tianleiwu Feb 29, 2020
b5f60cf
update with GPU run
tianleiwu Mar 3, 2020
c54723b
Remove OnnxRuntime inference tutorials.
tianleiwu Mar 23, 2020
f05a123
python version
tianleiwu Mar 23, 2020
c932d1b
remove onnxruntime Azure ML notebook
tianleiwu Mar 23, 2020
8ee34aa
update links
tianleiwu Mar 24, 2020
0b6a18e
Merge branch 'master' into master
tianleiwu Mar 24, 2020
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8 changes: 4 additions & 4 deletions README.md
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Expand Up @@ -66,9 +66,9 @@ Once you have an ONNX model, it can be scored with a variety of tools.
* [Serving PyTorch Models on AWS Lambda with Caffe2 & ONNX](https://machinelearnings.co/serving-pytorch-models-on-aws-lambda-with-caffe2-onnx-7b096806cfac)
* [MXNet to ONNX to ML.NET with SageMaker, ECS and ECR](https://cosminsanda.com/posts/mxnet-to-onnx-to-ml.net-with-sagemaker-ecs-and-ecr/) - external link
* [Convert CoreML YOLO model to ONNX, score with ONNX Runtime, and deploy in Azure](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/deployment/onnx/onnx-convert-aml-deploy-tinyyolo.ipynb)
* [Inference PyTorch Bert Model for High Performance in ONNX Runtime](tutorials/Inference-PyTorch-Bert-Model-for-High-Performance-in-ONNX-Runtime.ipynb)
* [Inference TensorFlow Bert Model for High Performance in ONNX Runtime](tutorials/Inference-TensorFlow-Bert-Model-for-High-Performance-in-ONNX-Runtime.ipynb)
* [Inference Bert Model for High Performance with ONNX Runtime on AzureML](tutorials/Inference-Bert-Model-for-High-Performance-with-ONNX-Runtime-on-AzureML.ipynb)
* [Inference PyTorch Bert Model for High Performance in ONNX Runtime](https://github.com/microsoft/onnxruntime/blob/master/onnxruntime/python/tools/bert/notebooks/PyTorch_Bert-Squad_OnnxRuntime_GPU.ipynb)
* [Inference TensorFlow Bert Model for High Performance in ONNX Runtime](https://github.com/microsoft/onnxruntime/blob/master/onnxruntime/python/tools/bert/notebooks/Tensorflow_Keras_Bert-Squad_OnnxRuntime_CPU.ipynb)
* [Inference Bert Model for High Performance with ONNX Runtime on AzureML](https://github.com/microsoft/onnxruntime/blob/master/onnxruntime/python/tools/bert/notebooks/Inference_Bert_with_OnnxRuntime_on_AzureML.ipynb)
* [Various Samples: Inferencing ONNX models using ONNX Runtime (Python, C#, C, Java, etc)](https://github.com/microsoft/onnxruntime/tree/master/samples)

### Serving
Expand All @@ -86,7 +86,7 @@ Once you have an ONNX model, it can be scored with a variety of tools.

### ONNX Custom Operators
* [How to export Pytorch model with custom op to ONNX and run it in ONNX Runtime](PyTorchCustomOperator/README.md)

## Other ONNX tools

* [Verifying correctness and comparing performance](tutorials/CorrectnessVerificationAndPerformanceComparison.ipynb)
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