#python #deep_learning #framework #inference #keras #layers #library #machine_learning #pytorch #shape #sota

https://github.com/szymonmaszke/torchlayers

#cplusplus #deep_learning #inference #inference_engine #openvino #performance

https://github.com/openvinotoolkit/openvino

#jupyter_notebook #computer_vision #deep_learning #inference #machine_learning #openvino

https://github.com/openvinotoolkit/openvino_notebooks

#cuda #training #inference #transformer #bart #beam_search #sampling #bert #multilingual_nmt #gpt_2 #diverse_decoding

https://github.com/bytedance/lightseq

#python #blockchain #deep_learning #distributed_training #edge_ai #federated_learning #inference_engine #machine_learning #marketplace #mlops #on_device_training #privacy #security

https://github.com/FedML-AI/FedML

#python #deep_learning #inference #pytorch

https://github.com/microsoft/DeepSpeed-MII

#python #bloom #deep_learning #gpt #inference #nlp #pytorch #transformer

https://github.com/huggingface/text-generation-inference

#python #graphcore #habana #inference #intel #onnx #onnxruntime #optimization #pytorch #quantization #tflite #training #transformers

https://github.com/huggingface/optimum

#jupyter_notebook #ai #aihub #argo #automl #gpt #inference #kubeflow #kubernetes #llmops #mlops #notebook #pipeline #pytorch #spark #vgpu #workflow

https://github.com/tencentmusic/cube-studio

#python #billion_parameters #compression #data_parallelism #deep_learning #gpu #inference #machine_learning #mixture_of_experts #model_parallelism #pipeline_parallelism #pytorch #trillion_parameters #zero

DeepSpeed is a powerful tool for training and using large artificial intelligence models quickly and efficiently. It allows you to train models with billions or even trillions of parameters, which is much faster and cheaper than other methods. With DeepSpeed, you can achieve significant speedups, reduce costs, and improve the performance of your models. For example, it can train ChatGPT-like models 15 times faster than current state-of-the-art systems. This makes it easier to work with large language models without needing massive resources, making AI more accessible and efficient for everyone.

https://github.com/microsoft/DeepSpeed