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A high-throughput and memory-efficient inference and serving engine for LLMs
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Development repository for the Triton language and compiler
Graph dump of torchbench models, huggingface models, and TIMM models.
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
A Python-level JIT compiler designed to make unmodified PyTorch programs faster.
functorch is JAX-like composable function transforms for PyTorch.
Examples for using ONNX Runtime for model training.
Ongoing research training transformer models at scale
End-to-End recipes for pre-training and fine-tuning BERT using Azure Machine Learning Service
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Open standard for machine learning interoperability
Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
A deep NLP library, based on Keras / tf, focused on question answering (but useful for other NLP too)
List of resources to get started with Deep Learning for NLP.
A tensorflow implementation of Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks
Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to …
An Open Source Machine Learning Framework for Everyone
For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.