#PyTorch Foundation Welcomes #vLLM and #DeepSpeed as Hosted Projects
https://thenewstack.io/pytorch-foundation-welcomes-vllm-and-deepspeed-as-hosted-projects/
#LLM@TutorialBTC
https://thenewstack.io/pytorch-foundation-welcomes-vllm-and-deepspeed-as-hosted-projects/
#LLM@TutorialBTC
The New Stack
PyTorch Foundation Welcomes vLLM and DeepSpeed as Hosted Projects
The PyTorch Foundation wants to be the home for all manner of open source AI projects.
Grad-CAM from Scratch with PyTorch Hooks
#Article #MachineLearning #PyTorch #Grad_CAM #Python
via Towards Data Science
#Article #MachineLearning #PyTorch #Grad_CAM #Python
via Towards Data Science
Towards Data Science
Grad-CAM from Scratch with PyTorch Hooks
A hands-on look at an explainable AI (XAI) technique that helps reveal why a convolutional neural network (CNN) made a particular decision
What PyTorch Really Means by a Leaf Tensor
#Article #Machine_Learning #PyTorch #Editors_Pick #Physics_Informed_Learning #Python #Pytorch #Tensor
via Towards Data Science
#Article #Machine_Learning #PyTorch #Editors_Pick #Physics_Informed_Learning #Python #Pytorch #Tensor
via Towards Data Science
Telegraph
What PyTorch Really Means by a Leaf Tensor
The secret life of leaves, gradients, and the mighty requires_grad flag The post What PyTorch Really Means by a Leaf Tensor appeared first on Towards Data Science. Generated by RSStT. The copyright…
A Caching Strategy for Identifying Bottlenecks on the Data Input Pipeline
#Article #Machine_Learning #Artificial_Intelligence #Deep_Dives #Mlops #Optimizaiton #Pytorch
via Towards Data Science
#Article #Machine_Learning #Artificial_Intelligence #Deep_Dives #Mlops #Optimizaiton #Pytorch
via Towards Data Science
Towards Data Science
A Caching Strategy for Identifying Bottlenecks on the Data Input Pipeline
PyTorch model performance analysis and optimization — Part 8
Pipelining AI/ML Training Workloads with CUDA Streams
#Article #Machine_Learning #Artificial_Intelligence #Cuda #Deep_Learning #Mlops #Pytorch
via Towards Data Science
#Article #Machine_Learning #Artificial_Intelligence #Cuda #Deep_Learning #Mlops #Pytorch
via Towards Data Science
Towards Data Science
Pipelining AI/ML Training Workloads with CUDA Streams
PyTorch Model Performance Analysis and Optimization — Part 9
Torchvista: Building an Interactive Pytorch Visualization Package for Notebooks
#Article #Artificial_Intelligence #Deep_Dives #Deep_Learning #Forward_Pass #Pytorch #Visualization
via Towards Data Science
#Article #Artificial_Intelligence #Deep_Dives #Deep_Learning #Forward_Pass #Pytorch #Visualization
via Towards Data Science
Telegraph
Torchvista: Building an Interactive Pytorch Visualization Pa…
Building a tool to interactively visualize the forward pass of any Pytorch model from within notebooks. The post Torchvista: Building an Interactive Pytorch Visualization Package for Notebooks…
Maximizing AI/ML Model Performance with PyTorch Compilation
#Article #MachineLearning #ArtificialIntelligence #DeepLearning #Python #Pytorch
via Towards Data Science
#Article #MachineLearning #ArtificialIntelligence #DeepLearning #Python #Pytorch
via Towards Data Science
Telegraph
Maximizing AI/ML Model Performance with PyTorch Compilation
Since its inception in PyTorch 2.0 in March 2023, the evolution of torch.compile has been one of the most exciting things to follow. Given that PyTorch’s popularity was due to its “Pythonic” nature, its ease of use, and its line-by-line (a.k.a., eager) execution…
Capturing and Deploying PyTorch Models with torch.export
#Article #ArtificialIntelligence #DeepDives #DeepLearning #ModelDeployment #Pytorch #Torchscript
via Towards Data Science
#Article #ArtificialIntelligence #DeepDives #DeepLearning #ModelDeployment #Pytorch #Torchscript
via Towards Data Science
Telegraph
Capturing and Deploying PyTorch Models with torch.export
A demonstration of PyTorch’s exciting new export feature on a HuggingFace model The post Capturing and Deploying PyTorch Models with torch.export appeared first on Towards Data Science. Generated by RSStT. The copyright belongs to the original author. Source