Combining the Best of Two Worlds: From TF-IDF to Llama LLMOpen Source Summit EuropeTalk by William Arias, Staff Developer Advocate at GitLab, on combining traditional NLP techniques and LLMs to solve hallucination issues and create robust spaCy applications.
Describing Images Fast and Slow: Quantifying and Predicting the Variation in Human Signals during Visuo-Linguistic ProcessesTakmaz, Pezzelle, Fernández (2024)We use the spaCy library for tokenization, part-of-speech tagging, and lemmatization of the words in the descriptions.
Simply Simplify LanguageInteractive app by the Canton of Zurich, Switzerland, using LLMs and spaCy to analyze and simplify institutional communication and make bureaucratic German more inclusive.
Slovak Dataset for Multilingual Question AnsweringHládek, Staš, Juhár, Koctúr (2023)We used the Prodigy annotation tool to annotate the questions and answers. One annotation task corresponds to one web application deployment and different configurations.
KI – Die künstlerische Intelligenz?Immergut Festival (German)Panelists are discussing the latest developments in Generative AI, hype vs. reality and what those new technologies mean for people, businesses, art, creativity and the music industry.
Deploying a Prodigy cloud service for Posh’s financial chatbotsA Prodigy case study of Posh AI's production-ready annotation platform and custom chatbot annotation tasks for banking customers.
T-RAG: Lessons from the LLM TrenchesFatehkia, Lucas, Chawla (2024)An important application area is question answering over private enterprise documents where the main considerations are data security, which necessitates applications that can be deployed on-prem, [and] limited computational resources. [...] In addition to retrieving contextual documents, we use the spaCy library with custom rules to detect named entities from the organization.
Image Captioning with Prodigy & PyTorchIn this video, we’ll show you how you can use Prodigy to script fully custom annotation workflows in Python, how to plug in your own machine learning models and how to mix and match different interfaces for your specific use case.