https://speakerdeck.com/danieldk 2023-12-19 04:49:04 -0500 spaCy is a Python library building for natural language processing pipelines. You can use spaCy for a wide variety of text-related tasks, such as identifying named entities, labeling spans, classifying documents, or uncovering the syntactic structure of text. The modular architecture of spaCy makes it possible to use a variety of neural network models, such as convolutional networks from Thinc, transformer models from Curated Transformers or Huggingface Transformers, and a wide variety of large language models (LLMs) using spacy-llm. In this talk, we will show you how you can use transformer models (from pretrained models such as XLM-RoBERTa to large language models like Llama2) to create state-of-the-art annotation pipelines for text annotation tasks such as named entity recognition. Daniël is a machine learning engineer at Explosion. He has worked on neural network models for natural language processing for over a decade. He enjoys everything from building new language processing components to squeezing the last bit of performance out of CUDA kernels. Madeesh is a machine learning engineer at Explosion who likes to tinker with the low-level nuts and bolts of code, be it neural networks or otherwise. He has also worked as an NLP researcher on language acquisition and question generation. spaCy is a Python library building for natural language processing pipelines. You can use spaCy for a wide variety of text-related tasks, such as identifying named entities, labeling spans, classifying documents, or uncovering the syntactic structure of text. The modular architecture of spaCy makes it possible to use a variety of neural network models, such as convolutional networks from Thinc, transformer models from Curated Transformers or Huggingface Transformers, and a wide variety of large language models (LLMs) using spacy-llm. In this talk, we will show you how you can use transformer models (from pretrained models such as XLM-RoBERTa to large language models like Llama2) to create state-of-the-art annotation pipelines for text annotation tasks such as named entity recognition. Daniël is a machine learning engineer at Explosion. He has worked on neural network models for natural language processing for over a decade. He enjoys everything from building new language processing components to squeezing the last bit of performance out of CUDA kernels. Madeesh is a machine learning engineer at Explosion who likes to tinker with the low-level nuts and bolts of code, be it neural networks or otherwise. He has also worked as an NLP researcher on language acquisition and question generation. Tue, 19 Dec 2023 00:00:00 -0500 https://speakerdeck.com/danieldk/state-of-the-art-transformer-pipelines-with-spacy https://speakerdeck.com/danieldk/state-of-the-art-transformer-pipelines-with-spacy