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Model Garden

Framework:
  • PyTorch
  • TensorFlow
  • PopART
Category:
  • Natural Language Processing
  • Computer Vision
  • Speech Processing
  • Probabilistic Modelling
  • Reinforcement Learning
  • Generative
  • Other
Filter:
  • Benchmarks

Training Models

BERT-Large Training

BERT-Large (Bidirectional Encoder Representations from Transformers) for NLP training on IPUs.

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  • Natural Language Processing
  • TensorFlow

BERT-Large Training

BERT-Large (Bidirectional Encoder Representations from Transformers) for NLP training on IPUs.

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  • Natural Language Processing
  • PopART

BERT-Large Training

BERT-Large (Bidirectional Encoder Representations from Transformers) for NLP training on IPUs.

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  • Natural Language Processing
  • PyTorch

BERT-Base Training

BERT-Base (Bidirectional Encoder Representations from Transformers) for NLP pre-training and training on IPUs.

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  • Natural Language Processing
  • PyTorch

BERT-Base Training

BERT-Base (Bidirectional Encoder Representations from Transformers) for NLP pre-training and training on IPUs.

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  • Natural Language Processing
  • TensorFlow

BERT-Base Training

BERT-Base (Bidirectional Encoder Representations from Transformers) for NLP pre-training and training on IPUs.

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  • Natural Language Processing
  • PopART

ResNet-50 Training

Image classification training on IPUs using the CNN (Convolutional Neural Network) model ResNet-50.

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  • Computer Vision
  • PyTorch

ResNet-50 Training

Image classification training on IPUs using the CNN (Convolutional Neural Network) model ResNet-50.

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  • Computer Vision
  • TensorFlow

EfficientNet-B0 Training

CNN (Convolutional Neural Network) image classification training on IPUs with EfficientNet.

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  • Computer Vision
  • PyTorch

EfficientNet-B4 Training

CNN (Convolutional Neural Network) image classification training on IPUs with EfficientNet.

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  • Computer Vision
  • TensorFlow

ResNeXt-101 Training

Image classification training on IPUs using the CNN (Convolutional Neural Network) model ResNeXt-101.

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  • Computer Vision
  • TensorFlow

MCMC Training

Markov Chain Monte Carlo (MCMC) training on IPUs using standard TensorFlow Probability.

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  • Probabilistic Modelling
  • TensorFlow

Deep Voice 3 Training

Text-To-Speech training on IPUs using a Convolutional Sequence Learning technique.

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  • Speech Processing
  • PopART

DIEN Training

DIEN (Deep Interest Evolution Network) training on IPUs - a recommendation model for click-through rate prediction.

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  • Other
  • TensorFlow

DIN Training

DIN (Deep Interest Network) training on IPUs - a recommendation model for click-through rate prediction.

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  • Other
  • TensorFlow

YOLOv3 Training

YOLOv3 - You Only Look Once - is a convolutional neural network model that performs object detection tasks on IPUs.

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  • Computer Vision
  • TensorFlow

MobileNetv3 Training

MobileNetv3 - Convolutional neural network training for classification, detection and segmentation.

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  • Computer Vision
  • PyTorch

Autoencoder Training

Custom autoencoder model on the IPU to train collaborative filtering in recommender systems.

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  • Generative
  • TensorFlow

Contrastive Divergence VAE Training

Train a Variational Autoencoder / Markov Chain Monte Carlo hybrid model on IPUs.

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  • Generative
  • TensorFlow

Reinforcement Learning Training

How to train a deep reinforcement learning model on multiple IPUs with synchronous data parallel training.

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  • Reinforcement Learning
  • TensorFlow

Sales Forecasting Training

How to train a sales forecasting machine learning model on Graphcore's IPUs.

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  • Probabilistic Modelling
  • TensorFlow

UNet Industrial Training

How to run a UNet Industrial training example for image segmentation

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  • Computer Vision
  • TensorFlow

Inference Models

BERT-Large Inference

BERT-Large (Bidirectional Encoder Representations from Transformers) for NLP inference on IPUs.

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  • Natural Language Processing
  • PopART

BERT-Base Inference

BERT-Base (Bidirectional Encoder Representations from Transformers) for NLP inference on IPUs.

View on GitHub
  • Natural Language Processing
  • PopART

ResNet-50 Inference

Image classification inference on IPUs using the CNN (Convolutional Neural Network) model ResNet-50.

View on GitHub
  • Computer Vision
  • PyTorch

ResNet-50 Inference

Image classification inference on IPUs using the CNN (Convolutional Neural Network) model ResNet-50.

View on GitHub
  • Computer Vision
  • TensorFlow

EfficientNet-B0/B4 Inference

CNN (Convolutional Neural Network) image classification inference on IPUs with EfficientNet.

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  • Computer Vision
  • PyTorch

ResNeXt-101 Inference

Image classification inference on IPUs using the CNN (Convolutional Neural Network) model ResNeXt-101.

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  • Computer Vision
  • PyTorch

ResNeXt-101 Inference

Image classification inference on IPUs using the CNN (Convolutional Neural Network) model ResNeXt-101.

View on GitHub
  • Computer Vision
  • TensorFlow

ResNeXt-101 Inference

Image classification inference on IPUs using the CNN (Convolutional Neural Network) model ResNeXt-101.

View on GitHub
  • Computer Vision
  • PopART

DIEN Inference

DIEN (Deep Interest Evolution Network) inference on IPUs - a recommendation model for click-through rate prediction.

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  • Other
  • TensorFlow

DIN Inference

DIN (Deep Interest Network) inference on IPUs - a recommendation model for click-through rate prediction.

View on GitHub
  • Other
  • TensorFlow

YOLOv3 Inference

YOLOv3 - You Only Look Once - is a convolutional neural network model that performs object detection tasks on IPUs.

View on GitHub
  • Computer Vision
  • TensorFlow

YOLOv4 Inference

YOLOv4 - You Only Look Once - is a convolutional neural network model that performs object detection tasks on IPUs.

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  • Computer Vision
  • PyTorch

MobileNetv2 Inference

MobileNetv2 - Convolutional neural network inference for classification, detection and segmentation.

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  • Computer Vision
  • TensorFlow

MobileNetv3 Inference

MobileNetv3 - Convolutional neural network inference for classification, detection and segmentation.

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  • Computer Vision
  • PyTorch

Autoencoder Inference

Custom autoencoder inference model on the IPU to perform collaborative filtering in recommender systems.

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  • Generative
  • TensorFlow
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