Language Modelling
Language modelling involves the development of statistical models that are able to predict the likelihood of a sequence of words occurring in a given context. These models are used in various natural language processing tasks such as speech recognition, machine translation, and text generation. The goal of language modelling is to capture the complex patterns and relationships within a language in order to improve the accuracy and fluency of automated systems that interact with human language.
External Links
- [kumo.ai] AI Platform - Improve my ML Model Performance, Predictive Graph Based Machine Learning For Marketing, Personalization, Platform, Pipelines, Fashion Retailers, B2C Ecommerce, Natural Language Processing, PYG MLOPS - Kumo
- [rwkv.net] GitHub - BlinkDL/ChatRWKV: ChatRWKV is like ChatGPT but powered by RWKV (100% RNN) language model, and open source.
- [modeling-languages.com] Modeling Languages - Latest news, tools and research reports
- [rwkv.com] RWKV Language Model
- [tcrs.io] TCRS 24 at ESWEEK | This workshop is meant as a forum for researchers interested in exploring models, languages, tools, and design methodologies for time-centric reactive systems. The event is part of ESWEEK.
- [sapling.ai] Language Model Copilot and API Toolkit | Sapling
- [ifml.org] IFML: The Interaction Flow Modeling Language | The OMG standard for front-end design
- [Convoluted.org] AI/ML Grooming and Pruning Techniques for Large Language Models