pytorch / workshops
This is a repository for all workshop related materials.
☆215Updated 10 months ago
Alternatives and similar repositories for workshops:
Users that are interested in workshops are comparing it to the libraries listed below
- A walkthrough of transformer architecture code☆339Updated last year
- Slides, notes, and materials for the workshop☆321Updated 9 months ago
- Source of the FSDL 2022 labs, which are at https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022-labs☆80Updated last year
- A performant, memory-efficient checkpointing library for PyTorch applications, designed with large, complex distributed workloads in mind…☆155Updated 3 months ago
- Complete deep learning project developed in Full Stack Deep Learning, Spring 2021☆448Updated 3 years ago
- Context Manager to profile the forward and backward times of PyTorch's nn.Module☆84Updated last year
- A library for distributed ML training with PyTorch☆366Updated 2 years ago
- All about the fundamental blocks of TF and JAX!☆276Updated 3 years ago
- Small scale distributed training of sequential deep learning models, built on Numpy and MPI.☆127Updated last year
- Amazon SageMaker Debugger provides functionality to save tensors during training of machine learning jobs and analyze those tensors☆161Updated 10 months ago
- Original transformer paper: Implementation of Vaswani, Ashish, et al. "Attention is all you need." Advances in neural information process…☆234Updated 11 months ago
- Examples of Machine Learning code using Comet.ml☆156Updated this week
- http://vlsiarch.eecs.harvard.edu/research/recommendation/☆133Updated 2 years ago
- Code and files to go along with CS329s machine learning model deployment tutorial.☆605Updated 2 years ago
- PyTorch RFCs (experimental)☆131Updated 7 months ago
- Interview Questions and Answers for Machine Learning Engineer role☆118Updated 2 years ago
- PDFs and Codelabs for the Efficient Deep Learning book.☆191Updated last year
- Annotations of the interesting ML papers I read☆237Updated 3 weeks ago
- Software Architecture for ML engineers☆399Updated 2 years ago
- Resource-adaptive cluster scheduler for deep learning training.☆436Updated 2 years ago
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆189Updated this week
- Cataloging released Triton kernels.☆212Updated 2 months ago
- Toy example of an applied ML pipeline for me to experiment with MLOps tools.☆208Updated 3 years ago
- Home for OctoML PyTorch Profiler☆108Updated last year
- PyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.☆260Updated 4 years ago
- Ray tutorials from Anyscale☆604Updated last year
- Outlining techniques for improving the training performance of your PyTorch model without compromising its accuracy☆126Updated last year
- A collection of Machine Learning examples to get started with deploying RAPIDS in the Cloud☆140Updated 4 months ago
- Automatic GPU+CPU memory profiling, re-use and memory leaks detection using jupyter/ipython experiment containers☆215Updated last year
- ☆67Updated last year