Training and Inference of LLMs with PyTorch Fully Sharded Data Parallel and Better Transformer
In this blog we show how to perform efficient and optimized distributed training and inference of large language models using PyTorch’s Fully Sharded Data Parallel and Better Transformer implementations, on the Spark platform. In this implementation, we combine Microsoft Fabric for data preparation and model inference, and Azure Databricks for model training, having all our data under Microsoft Fabric’s OneLake. The code for this blog is available at this GitHub repository, as a series of PySpark notebooks for Microsoft Fabric and Azure Databricks.Great Way to Start with Deep Learning: Introducing PyTorch Courses on Microsoft Learn
Deep Learning is one of the most popular topics amongst both students and software developers. We have recently released a learning path on Microsoft Learn that will help you get started with Deep Learning, based on one of the most popular frameworks: PyTorch.Interview with Jeremy Howard Fast.ai AI Application without a PhD
Fast.ai has made it their mission to make deep learning as accessible as possible, and in this interview fast.ai co-founder Jeremy Howard explains how to use their free software and courses to become an effective deep learning practitioner.
Is ORTModule supporting only NLP models for now?
Hello, Can someone please let me know if is this feasible to use ORTModule with Pytorch models like Deeplab/ Fcos, FasterRCNN or Maskrcnn?. Examples and documentation only mentions NLP models. I however did try to wrap these models into an ORTModule but it did not work. At the begging the errors were related to missing operators that I had to register as custom operators but the last error error shown is: errors.SymbolicValueError( torch.onnx.errors.SymbolicValueError: ONNX export does NOT support exporting bitwise OR for non-boolean input values . Should these wraps work? Or is it these Deep Learning models are still not supported for ortModule? Appreciate your help, Zazhil-haPerformance of running NNs across Azure GPU Series Data Science Virtual Machines
First published on MSDN on Nov 22, 2017 One of the question I regularly get, from Student and academics is, Which NN runs the best on Azure?Caffe2MXNetGluonCNTKPyTorchTensorflowKeras(CNTK)ChainerKeras(TF)Lasagne(Theano)Keras(Theano)NNs on AzureSo Azure has lots of support for these including prebuilt Azure Batch shipyard container see https://github.
