onnxruntime
onnx-tensorrt
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onnxruntime | onnx-tensorrt | |
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53 | 4 | |
12,583 | 2,745 | |
4.0% | 2.0% | |
10.0 | 4.1 | |
3 days ago | 15 days ago | |
C++ | C++ | |
MIT License | Apache License 2.0 |
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onnxruntime
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AI Inference now available in Supabase Edge Functions
Embedding generation uses the ONNX runtime under the hood. This is a cross-platform inferencing library that supports multiple execution providers from CPU to specialized GPUs.
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Deep Learning in JavaScript
tfjs is dead, looking at the commit history. The standard now is to convert PyTorch to onnx, then use onnxruntime (https://github.com/microsoft/onnxruntime/tree/main/js/web) to run the model on the browsdr.
- FLaNK Stack 05 Feb 2024
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Vcc – The Vulkan Clang Compiler
- slang[2] has the potential, but the meta programming part is not as strong as C++, existing libraries cannot be used.
The above conclusion is drawn from my work https://github.com/microsoft/onnxruntime/tree/dev/opencl, purely nightmare to work with thoes drivers and jit compilers. Hopefully Vcc can take compute shader more seriously.
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Oracle-samples/sd4j: Stable Diffusion pipeline in Java using ONNX Runtime
I did. It depends what you want, for an overview of how ONNX Runtime works then Microsoft have a bunch of things on https://onnxruntime.ai, but the Java content is a bit lacking on there as I've not had time to write much. Eventually I'll probably write something similar to the C# SD tutorial they have on there but for the Java API.
For writing ONNX models from Java we added an ONNX export system to Tribuo in 2022 which can be used by anything on the JVM to export ONNX models in an easier way than writing a protobuf directly. Tribuo doesn't have full coverage of the ONNX spec, but we're happy to accept PRs to expand it, otherwise it'll fill out as we need it.
- Mamba-Chat: A Chat LLM based on State Space Models
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VectorDB: Vector Database Built by Kagi Search
What about models besides GPT? Most of the popular vector encoding models aren't using this architecture.
If you really didn't want PyTorch/Transformers, you could consider exporting your models to ONNX (https://github.com/microsoft/onnxruntime).
- ONNX runtime: Cross-platform accelerated machine learning
- Onnx Runtime: “Cross-Platform Accelerated Machine Learning”
onnx-tensorrt
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Introducing Cellulose - an ONNX model visualizer with hardware runtime support annotations
[1] - We use onnx-tensorrt for this TensorRT compatibility checks.
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[P] [D]How to get TensorFlow model to run on Jetson Nano?
Conversion was done from Keras Tensorflow using to ONNX https://github.com/onnx/keras-onnx followed by ONNX to TensorRT using https://github.com/onnx/onnx-tensorrt The Python code used for inference using TensorRT can be found at https://github.com/jonnor/modeld/blob/tensorrt/tensorrtutils.py
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New to this: could I use Nvidia Nano + lobe?
Hi! You can run the models trained in Lobe on the Jetson Nano, either through TensorFlow (https://docs.nvidia.com/deeplearning/frameworks/install-tf-jetson-platform/index.html), ONNX runtime (https://elinux.org/Jetson_Zoo#ONNX_Runtime), or running ONNX on TensorRT (https://github.com/onnx/onnx-tensorrt).
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How to install ONNX-TensorRT Python Backend on Jetpack 4.5
Hello, I would like to install https://github.com/onnx/onnx-tensorrt from a package because compiling is a lot of complicated. Is there any source for this package?
What are some alternatives?
onnx - Open standard for machine learning interoperability
TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
onnx-simplifier - Simplify your onnx model
jetson-inference - Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
ONNX-YOLOv7-Object-Detection - Python scripts performing object detection using the YOLOv7 model in ONNX.
server - The Triton Inference Server provides an optimized cloud and edge inferencing solution.
onnx-tensorflow - Tensorflow Backend for ONNX
deepC - vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers
MLflow - Open source platform for the machine learning lifecycle
keras-onnx - Convert tf.keras/Keras models to ONNX
TensorRT - PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
modeld - Self driving car lane and path detection