Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
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May 26, 2022 - Python
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tpu
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GPT2 for Multiple Languages, including pretrained models. GPT2 多语言支持, 15亿参数中文预训练模型
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May 26, 2022 - Python
Everything we actually know about the Apple Neural Engine (ANE)
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May 3, 2022
Julia on TPUs
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Dec 18, 2020 - Julia
Implementation of a Tensor Processing Unit for embedded systems and the IoT.
linux
iot
fpga
zynq
tensorflow
assembly
vhdl
embedded-systems
internet-of-things
hardware-architectures
verilog
xilinx
vivado
tensor
hardware-designs
hardware-acceleration
fpga-accelerator
hardware-description-language
ip-core
tpu
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Jan 5, 2019 - VHDL
Free TPU for FPGA with Lenet, MobileNet, Squeezenet, Resnet, Inception V3, YOLO V3, and ICNet. Deep learning acceleration using Xilinx zynq (Zedboard or ZC702 ) or kintex-7 to solve image classification, detection, and segmentation problem.
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Apr 2, 2019 - Shell
TPU ile Yapay Sinir Ağlarınızı Çok Daha Hızlı Eğitin
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May 19, 2019 - Jupyter Notebook
Simple and efficient RevNet-Library for PyTorch with XLA and DeepSpeed support and parameter offload
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Feb 27, 2022 - Python
Unofficial implementation of Octave Convolutions (OctConv) in TensorFlow / Keras.
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Feb 16, 2020 - Jupyter Notebook
Dual Edge TPU Adapter to use it on a system with single PCIe port on m.2 A/B/E/M slot
home-assistant
m2
coral
tpu
tensorflow-lite
tpu-benchmarks
tpu-acceleration
edge-ai
edgetpu
edge-tpu
m2-module
coral-tpu
pcie-card
pcie-interface
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Feb 15, 2022
EfficientNet, MobileNetV3, MobileNetV2, MixNet, etc in JAX w/ Flax Linen and Objax
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May 31, 2021 - Python
Everything you want to know about Google Cloud TPU
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May 16, 2022 - Python
Edge TPU Accelerator / Multi-TPU + MobileNet-SSD v2 + Python + Async + LattePandaAlpha/RaspberryPi3/LaptopPC
python
opencv
google
raspberrypi
lattepanda
tpu
tensorflowlite
mobilenetv2
colaboratory
mobilenetssd
tensorflow-lite
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Aug 12, 2019 - Python
EvoPose2D is a two-stage human pose estimation model that was designed using neuroevolution. It achieves state-of-the-art accuracy on COCO.
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Oct 20, 2021 - Python
Repository for Google Summer of Code 2019 https://summerofcode.withgoogle.com/projects/#4662790671826944
tensorflow
keras
super-resolution
tpu
googlesummerofcode
onnx
tensorflow-datasets
tensorflow-2
tf-hub
tensorflow-2-sample
enhanced-super-resolution
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Aug 17, 2021 - Python
A FPGA Based CNN accelerator, following Google's TPU V1.
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Jul 25, 2019 - C++
TF2 implementation of knowledge distillation using the "function matching" hypothesis from https://arxiv.org/abs/2106.05237.
tensorflow
keras
vision
image-classification
transfer-learning
knowledge-distillation
tpu
bit-resnet
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Sep 24, 2021 - Jupyter Notebook
DECIMER 1.0: Deep Learning for Chemical Image Recognition using Transformers
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May 19, 2022 - Python
Train DCGAN with TPUs on Google Cloud
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Dec 30, 2018 - Python
Small-scale Tensor Processing Unit built on an FPGA
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Aug 4, 2019 - Verilog
Testing framework for Deep Learning models (Tensorflow and PyTorch) on Google Cloud hardware accelerators (TPU and GPU)
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May 26, 2022 - Jsonnet
Tutorial to pretrain & fine-tune a 🤗 Flax T5 model on a TPUv3-8 with GCP
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Mar 9, 2022 - Python
Website for Eclipse ioFog, a distributed Edge Compute Network (ECN) platform
kubernetes
yaml
edge
gpu-acceleration
vpu
jetson-tx2
edge-computing
eclipse-iot
myriad
tpu
neural-compute-stick
iofog
jetsontx2
jetson-agx-xavier
tpu-acceleration
jetson-nano
neural-compute-stick-2
eclipse-edge
edge-native
edge-compute-network
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May 10, 2022 - JavaScript
Automatic GPU, TPU, FPGA, Xeon Phi, Multithreaded, Distributed, etc. offloading for scientific machine learning (SciML) and differential equations
fpga
gpu
multiprocessing
multithreading
distributed
differential-equations
xeon-phi
tpu
scientific-machine-learning
sciml
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Dec 3, 2021 - Julia
BERT Model Fine-tuning on Quora Questions Pairs
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Jun 11, 2019 - Jupyter Notebook
TF2 implementation of PointNet for segmenting point clouds
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Nov 16, 2021 - Python
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We would like to forward a particular 'key' column which is part of the features to appear alongside the predictions - this is to be able to identify to which set of features a particular prediction belongs to. Here is an example of predictions output using the tensorflow.contrib.estimator.multi_class_head: