Pinned Repositories
azure-docs
Open source documentation of Microsoft Azure
azureml-examples
Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
MachineLearningNotebooks-1
Python notebooks with ML and deep learning examples with Azure Machine Learning | Microsoft
Many-Models
Implement many models for ML in Azure
Megatron-DeepSpeed
Ongoing research training transformer language models at scale, including: BERT & GPT-2
Megatron-DeepSpeed-AML
Ongoing research training transformer language models at scale, including: BERT & GPT-2
onnxruntime-training-examples
Examples for using ONNX Runtime for model training.
Synapse
Samples for Azure Synapse Analytics
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
savitamittal1's Repositories
savitamittal1/azure-docs
Open source documentation of Microsoft Azure
savitamittal1/azureml-examples
Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
savitamittal1/DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
savitamittal1/MachineLearningNotebooks-1
Python notebooks with ML and deep learning examples with Azure Machine Learning | Microsoft
savitamittal1/Many-Models
Implement many models for ML in Azure
savitamittal1/Megatron-DeepSpeed
Ongoing research training transformer language models at scale, including: BERT & GPT-2
savitamittal1/Megatron-DeepSpeed-AML
Ongoing research training transformer language models at scale, including: BERT & GPT-2
savitamittal1/onnxruntime-training-examples
Examples for using ONNX Runtime for model training.
savitamittal1/Synapse
Samples for Azure Synapse Analytics
savitamittal1/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
savitamittal1/tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.