pnnx/pnnx

Support PyTorch model conversion with LiteRT.

PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT

A tool for converting ONNX files to LiteRT/TFLite/TensorFlow, PyTorch native code (nn.Module), TorchScript (.pt), state_dict (.pt), Exported Program (.pt2), and Dynamo ONNX. It also supports direct conversion from LiteRT to PyTorch.

Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX

Serve, optimize and scale PyTorch models in production

PyTorch native quantization for training and inference

Open standard for machine learning interoperability

A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.