InsightFace REST API for easy deployment of face recognition services with TensorRT in Docker.
Conversion to/from half-precision floating point formats
Deploy stable diffusion model with onnx/tenorrt + tritonserver
IEEE 754 half-precision floating-point ponyfill
👀 Apply YOLOv8 exported with ONNX or TensorRT(FP16, INT8) to the Real-time camera
CPP20 implementation of a 16-bit floating-point type mimicking most of the IEEE 754 behavior. Single file and header-only.
Round matrix elements to lower precision in MATLAB
Pytorch implementation of DreamerV2: Mastering Atari with Discrete World Models, based on the original implementation
Optimised Caffe with OpenCL supporting for less powerful devices such as mobile phones
IEEE 754-style floating-point converter
Let's train CIFAR 10 Pytorch with Half-Precision!
Export pytorch model to ONNX and convert ONNX from float32 to float 16
A flexible utility for converting tensor precision in PyTorch models and safetensors files, enabling efficient deployment across various platforms.
apextrainer is an open source toolbox for fp16 trainer based on Detectron2 and Apex
Converts a floating-point number or hexadecimal representation of a floating-point numbers into various formats and displays them into binary/hexadecimal.
Transformer implementation in pytorch trained on NVIDIA A100 in fp16
llama 3.2 1b fp16 cpu inference in one file of pure VB.NET
A modular, accelerator-ready machine learning framework built in Go that speaks float8/16/32/64. Designed with clean architecture, strong typing, and native concurrency for scalable, production-ready AI systems. Ideal for engineers who value simplicity, speed, and maintainability.
Simple Example of Pytorch -> TensorRT and Inference
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