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Model Garden

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Dolly 2.0 – The World’s First, Truly Open Instruction-Tuned LLM on IPUs – Inference

OpenAssistant Pythia 12B is an open-source and commercially usable chat-based assistant model trained on the OpenAssistant Conversations Dataset (OASST1)

Speech Transcription on IPUs using OpenAI's Whisper - Inference

Run Meta’s latest Open Source Large Language Model Inference on IPUs

The popular latent diffusion model for generative AI with support for text-to-image on IPUs using Hugging Face Optimum.

The popular latent diffusion model for generative AI with support for text-to-image on IPUs using Hugging Face Optimum.

The popular latent diffusion model for generative AI with support for image-to-image on IPUs using Hugging Face Optimum.

The popular latent diffusion model for generative AI with support for inpainting on IPUs using Hugging Face Optimum.

Text entailment on IPU using GPT-J 6B on PyTorch using fine-tuning.

Text generation on IPU using GPT-J 6B on PyTorch for inference.

Training a GNN to do Fraud Detection using Relational Graph Convolution Network (RGCN) on IPUs with PyG (PyTorch Geometric)

GPT-3 (Generative Pretrained Transformer 3) is a state-of-the-art language processing AI model developed by OpenAI.

GPT-3 (Generative Pretrained Transformer 3) is a state-of-the-art language processing AI model developed by OpenAI.

GPT2-L training in PyTorch leveraging the Hugging Face Transformers library.

GPT2-L inference in PyTorch leveraging the Hugging Face Transformers library.

GPT2-M training in PyTorch leveraging the Hugging Face Transformers library.

HuggingFace Optimum implementation for fine-tuning a GPT2-Medium transformer model.

GPT2-M inference in PyTorch leveraging the Hugging Face Transformers library.

GPT2-S training in PyTorch leveraging the Hugging Face Transformers library.

HuggingFace Optimum implementation for fine-tuning a GPT2-Small transformer model.

GPT2-S inference in PyTorch leveraging the Hugging Face Transformers library.

Flan-T5-Large/XL inference on IPUs with Hugging Face

Summarization on IPU using T5 Small with Hugging Face Optimum - Fine-Tuning

Machine Translation on IPUs using MT5-Small with Hugging Face - Fine-tuning

Zero-Shot Text Classification on IPUs using MT5-Large with Hugging Face - Inference

A hybrid GNN/Transformer for training Molecular Property Prediction using IPUs on the PCQM4Mv2 dataset. Winner of the Open Graph Benchmark Large-Scale Challenge.

A hybrid GNN/Transformer for Molecular Property Prediction inference using IPUs trained on the PCQM4Mv2 dataset. Winner of the Open Graph Benchmark Large-Scale Challenge.

Knowledge graph embedding (KGE) for link-prediction training on IPUs using Poplar with the WikiKG90Mv2 dataset. Winner of the Open Graph Benchmark Large-Scale Challenge.

Knowledge graph embedding (KGE) for link-prediction inference on IPUs using Poplar with the WikiKG90Mv2 dataset. Winner of the Open Graph Benchmark Large-Scale Challenge.

Knowledge graph embedding (KGE) for link-prediction training on IPUs using PyTorch with the WikiKG90Mv2 dataset. Winner of the Open Graph Benchmark Large-Scale Challenge.

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

BERT-Large (Bidirectional Encoder Representations from Transformers) using TensorFlow 1 for NLP training on IPUs.

BERT-Large (Bidirectional Encoder Representations from Transformers) for NLP inference on IPUs with TensorFlow 1.

BERT-Large (Bidirectional Encoder Representations from Transformers) using TensorFlow 2 for NLP training on IPUs.

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

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

HuggingFace Optimum implementation for fine-tuning a BERT-Large transformer model.

HuggingFace Optimum implementation for pre-training a BERT-Large transformer model.

DistilBERT is a small, fast, cheap and light Transformer model trained by distilling BERT base using Hugging Face Optimum on IPUs.

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

BERT-Base (Bidirectional Encoder Representations from Transformers) using TensorFlow 2 for NLP training on IPUs.

BERT-Base (Bidirectional Encoder Representations from Transformers) using TensorFlow 1 for NLP training on IPUs.

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

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

BERT-Base pre-training and SQuAD fine-tuning using Baidu's PaddlePaddle framework on IPUs.

HuggingFace Optimum implementation for pretraining a BERT-Base transformer model using bert-based-uncased datasets.

HuggingFace Optimum implementation for fine-tuning a BERT-Base transformer model using bert-base-uncased on the squad dataset.

HuggingFace Optimum implementation for training RoBERTa-Large - a transformer model for sequence classification, token classification or question answering.

HuggingFace Optimum implementation for fine-tuning RoBERTa-Base on the squad dataset for text generation and comprehension tasks

HuggingFace Optimum implementation for fine-tuning RoBERTa-Base on the squad_v2 dataset for text generation and comprehension tasks

HuggingFace Optimum implementation for fine-tuning LXMERT on the gqa-lxmert dataset for learning vision-and-language cross-modality representations.

HuggingFace Optimum implementation for training DeBERTa - a transformer models that improves BERT and RoBERTa models using disentangled attention and enhanced mask decoder.

HuggingFace Optimum implementation for fine-tuning LXMERT on the vqa-lxmert dataset for learning vision-and-language cross-modality representations.

SQuAD and MNLI on IPUs using DeBERTa with Hugging Face - Inference

HuggingFace Optimum implementation for training HuBERT (Hidden-Unit BERT) for self-supervised speech representation learning approach.

HuggingFace Optimum implementation for training BART - a transformer model for text generation and comprehension tasks

GroupBERT - an enhanced transformer architecture with efficient grouped structures in TensorFlow 1.

New BERT packing algorithm that removes padding for more efficient training in PyTorch.

New BERT packing algorithm that removes padding for more efficient training in PopART.

New BERT packing algorithm that removes padding for more efficient fine-tuning in Hugging Face.

New BERT packing algorithm that removes padding for more efficient inference in Hugging Face.

A variant of the conformer model based on WeNet (not ESPnet) using PyTorch which uses a hybrid CTC/attention architecture with transformer or conformer as an encoder.

CLIP (Contrastive Language-Image Pre-Training) - a neural network trained on a variety of (image, text) pairs using PyTorch.

ViT (Vision Transformer) fine-tuning in PyTorch using Hugging Face transformers.

ViT (Vision Transformer) pretraining in PyTorch using Hugging Face transformers.

HuggingFace Optimum implementation for fine-tuning a ViT (vision transformer) model.

Self-supervised Vision Transformer model for training in PyTorch.

YOLOv3 - You Only Look Once - a convolutional neural network model that performs object detection tasks on IPUs using TensorFlow 1.