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Pretrain Transformers Models in PyTorch Using Hugging Face Transformers
This notebook is used to pretrain transformers models using Hugging Face on your own custom dataset. What do I mean by pretrain transformers? The definition of pretraining is to train in advance. That is exactly what I mean! Train a transformer model to use it as a pretrained transformers model which can be used to fine-tune it on a specific task!…
Top Applications of Graph Neural Networks 2021
At the beginning of the year, I have a feeling that Graph Neural Nets (GNNs) became a buzzword. As a researcher in this field, I feel a little bit proud (at least not ashamed) to say that I work on this. It was not always the case: three years ago when I was talking to…
Leading AI & Machine Learning Research Trends 2021
To help you stay well prepared for 2021, we have summarized the latest trends across different research areas, including natural language processing, conversational AI, computer vision, and reinforcement learning. We also suggest key research papers in different areas that we think are representative of the latest advances. Subscribe to our AI Research mailing list at…
TOPBOTS Guide to NeurIPS 2020
This year’s Annual Conference on Neural Information Processing (NeurIPS 2020) is held 100% virtually from December 6th to 12th, 2020. Historically NeurIPS sells out quickly and can be a challenge to register for. But, this year’s virtual format welcomes everyone with an affordable ticket price of $100. 2020 is our third year of TOPBOTS covering…
2020’s Top AI & Machine Learning Research Papers
Despite the challenges of 2020, the AI research community produced a number of meaningful technical breakthroughs. GPT-3 by OpenAI may be the most famous, but there are definitely many other research papers worth your attention. For example, teams from Google introduced a revolutionary chatbot, Meena, and EfficientDet object detectors in image recognition. Researchers from Yale…
GPT-3 & Beyond: 10 NLP Research Papers You Should Read
NLP research advances in 2020 are still dominated by large pre-trained language models, and specifically transformers. There were many interesting updates introduced this year that have made transformer architecture more efficient and applicable to long documents. Another hot topic relates to the evaluation of NLP models in different applications. We still lack evaluation approaches that…
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