nanoVLM: The simplest repository to train your VLM in pure PyTorch

Quanto: a PyTorch quantization backend for Optimum

TorchKM: A GPU-Oriented Library for Kernel Learning and Model Selection

arXiv:2606. 06742v1 Announce Type: new Abstract: TorchKM is an open-source library for kernel machines, including support vector machines, kernel logistic regression, and kernel quantile regression, with GPU acceleration.

OpenAI standardizes on PyTorch

We are standardizing OpenAI’s deep learning framework on PyTorch.

Accelerating PyTorch distributed fine-tuning with Intel technologies

ElemeNet: Multiscale Molecular Machine Learning with Uncertainty Quantification Across the Periodic Table

arXiv:2606. 30961v1 Announce Type: cross Abstract: Advances in deep learning architectures and representations have enabled ML-driven chemical property prediction, but state-of-the-art (SOTA) models have remained largely confined to independent codebases and lack support for diverse chemical species.

Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels

arXiv:2607. 24762v1 Announce Type: new Abstract: Machine learning models are increasingly embedded in everyday software, and most of their runtime is spent in a small set of compute kernels such as matrix multiplication, convolution, and normalization.

Profiling in PyTorch (Part 2): From nn.Linear to a Fused MLP

Scikit-fingerprints: Python library for scikit-learn compatible molecular fingerprints and chemoinformatics

arXiv:2608. 02027v1 Announce Type: new Abstract: We present scikit-fingerprints, a comprehensive, fully scikit-learn compatible library for molecular machine learning in Python, based on RDKit.

torchsom: The Reference PyTorch Library for Self-Organizing Maps

arXiv:2510. 11147v2 Announce Type: replace-cross Abstract: This paper introduces torchsom, an open-source Python library that provides a reference implementation of the Self-Organizing Map (SOM) in PyTorch.

From PyTorch DDP to Accelerate to Trainer, mastery of distributed training with ease

Profiling in PyTorch (Part 1): A Beginner's Guide to torch.profiler

Accelerate Large Model Training using PyTorch Fully Sharded Data Parallel