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Toolkit for efficient experimentation with Speech Recognition, Text2Speech and NLP

Microsoft Automatic Mixed Precision Library

Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.

[CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision

Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation

[ICLR'25] ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation

High Resolution Style Transfer in PyTorch with Color Control and Mixed Precision 🎨

Training with FP16 weights in PyTorch

NAACL '24 (Best Demo Paper RunnerUp) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference

基于tensorflow1.x的预训练模型调用，支持单机多卡、梯度累积，XLA加速，混合精度。可灵活训练、验证、预测。

BitPack is a practical tool to efficiently save ultra-low precision/mixed-precision quantized models.

🎯 Gradient Accumulation for TensorFlow 2

[ECCV24] MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization

Extremely simple and understandable GPT2 implementation with minor tweaks

Let's train CIFAR 10 Pytorch with Half-Precision!

A Python package for simulating low precision arithmetic in scientific computing and machine learning

PyTorch RNet implementation with Distributed and Mixed-Precision training support.

A deepfake face detection system using transfer learning with Xception CNN. Trained on real and fake face datasets using data augmentation, mixed precision, and GPU acceleration. Accurately classifies facial images as real or fake with high confidence. Ideal for media forensics.

[CVPR 2016]You Only Look Once: Unified, Real-Time Object Detection