NLP | Solving
Source: • Solving Natural Language problems with sca...
The video was published under the license of the Creative Commons Attribution license (reuse allowed) and is reposted for educational purposes.
In this talk Álvaro will introduce the concept of language models, and review some of the state of the art approaches to building such models (BERT, GPT-2 and XLNet), delving into the network architecture and training strategies used in them. Then he will move on to show how these pre-trained language models can be fine-tuned to small datasets to produce high quality results in downstream NLP tasks, by making use of the open-source PyTorch-Transformers library (https://github.com/huggingface/transf.... This library is built on top of the PyTorch deep learning framework, and allows loading pre-trained language models and fine-tuning them easily. This talk will be focused on the theoretical grounds of these methods and on his practical experience in applying them.
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