An executor that loads ONNX models and embeds documents using the ONNX runtime.
from jina import Flow
f = Flow().add(uses='jinahub+docker://ONNXEncoder')
from jina import Flow
f = Flow().add(uses='jinahub://ONNXEncoder')
__init__ args & kwargs, use .add(..., uses_with: {'key': 'value'}).add(..., uses_metas: {'key': 'value})scc4onnx Very simple NCHW and NHWC conversion tool for ONNX. Change to the specified input order for each and every input OP. Also, change the channel
sne4onnx A very simple tool for situations where optimization with onnx-simplifier would exceed the Protocol Buffers upper file size limit of 2GB, or
sog4onnx Simple ONNX operation generator. Simple Operation Generator for ONNX. https://github.com/PINTO0309/simple-onnx-processing-tools Key concept V
ailia-models-tflite Quantized tflite models for ailia TFLite Runtime About ailia TFLite Runtime ailia TF Lite Runtime is a TensorFlow Lite compatible
FMEN Lowest memory consumption and second shortest runtime in NTIRE 2022 on Efficient Super-Resolution. Our paper: Fast and Memory-Efficient Network T
MMdnn MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model manage
PyTorch Infer Utils This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model infer
torchtyping Type annotations for a tensor's shape, dtype, names, ... Turn this: def batch_outer_product(x: torch.Tensor, y: torch.Tensor) - torch.Ten
nvidia-container-runtime A modified version of runc adding a custom pre-start hook to all containers. If environment variable NVIDIA_VISIBLE_DEVICES i
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v0.2.0 - 17.02.2022Migration to jina v3.0
jina v3.0v0.1.0 - 24.12.2021ONNXEncoder initial version
Deep Learning for Human Part Discovery in Images - Chainer implementation NOTE: This is not official implementation. Original paper is Deep Learning f
写在前面 利用TensorRT加速推理速度是以时间换取精度的做法，意味着在推理速度上升的同时将会有精度的下降，不过不用太担心，精度下降微乎其微。此外，要有NVIDIA显卡，经测试，CUDA10.2可以支持20系列显卡及以下，30系列显卡需要CUDA11.x的支持，并且目前有bug。 默认你已经完成了
spacy-huggingface-hub: Push your spaCy pipelines to the Hugging Face Hub This package provides a CLI command for uploading any trained spaCy pipeline
zalando-pytorch PyTorch experiments with the Zalando fashion-mnist dataset Project Organization ├── LICENSE ├── Makefile - Makefile with co
LicensePlate_Project 🚗 🚙 [Project] 2021.02 ~ 2021.09 License Plate Detection Application Overview 1. 데이터 수집 및 라벨링 차량 번호판 이미지를 직접 수집하여 각 이미지에 대해 '번호판
SRAugmentation Augmentation for Single-Image-Super-Resolution Implimentation CutBlur Cutout CutMix Cutup CutMixup Blend RGBPermutation Identity OneOf
MKGFormer Code for the SIGIR 2022 paper "Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion" Model Architecture Illu
如何用10天吃掉pyspark？ 🔥 🔥 《10天吃掉那只pyspark》 🚀
WECHSEL Code for WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models. arXiv: https://arx
How to transform a cow into spherical harmonics ? Spot the cow, from Keenan Crane's blog Context In the field of Deep Learning, training on images or
MSAD Multi-Scale Aligned Distillation for Low-Resolution Detection Lu Qi*, Jason Kuen*, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya J
Bangalore-House-Price-Prediction An end-to-end regression problem of predicting the price of properties in Bangalore. Deployed in Heroku using Flask.
3d-pose-baseline This is the code for the paper Julieta Martinez, Rayat Hossain, Javier Romero, James J. Little. A simple yet effective baseline for 3
MuarAugment Description MuarAugment is a package providing the easiest way to a state-of-the-art data augmentation pipeline. How to use You can instal
Simple Transformer An implementation of the "Attention is all you need" paper without extra bells and whistles, or difficult syntax. Note: The only ex
Effect of Different Encodings and Distance Functions on Quantum Instance-based Classifiers The repository contains the code to reproduce the experimen
Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee
LMSOC: An Approach for Socially Sensitive Pretraining Code for reproducing the paper LMSOC: An Approach for Socially Sensitive Pretraining to appear a
model_galaxy Modelisation on galaxy evolution using PEGASE-HR This is a labwork done in internship at IAP directed by Damien Le Borgne (https://github
TUPE PyTorch implementation of Rethinking Positional Encoding in Language Pre-training. Quickstart Clone this repository. git clone https://github.com
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