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models, also with Git-based version control; datasets, mainly in text, images, and audio; web applications ("spaces" and "widgets"), intended for small-scale demos of machine learning applications. There are numerous pre-trained models that support common tasks in different modalities, such as:
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text. This page lists notable large language models.
Text Classification 1990 [280] [281] Bupa Medical Research Ltd. Thyroid Disease Dataset 10 databases of thyroid disease patient data. None. 7200 Text Classification 1987 [282] [283] R. Quinlan Mesothelioma Dataset Mesothelioma patient data. Large number of features, including asbestos exposure, are given. 324 Text Classification 2016 [284] [285]
BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [ 3 ]
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text. The largest and most capable LLMs are generative pretrained transformers (GPTs).
Unlike previous models, BERT is a deeply bidirectional, unsupervised language representation, pre-trained using only a plain text corpus. Context-free models such as word2vec or GloVe generate a single word embedding representation for each word in the vocabulary, whereas BERT takes into account the context for each occurrence of a given word ...
In the same month, February 2023, MindsDB announced its integration with Hugging Face and OpenAI that would allow natural language processing and generative AI models into their database via API accessible with SQL requests. This integration enabled advanced text classification, sentiment analysis, emotion detection, translation, and more.
A foundation model, also known as large X model (LxM), is a machine learning or deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. [1] Generative AI applications like Large Language Models are often examples of foundation models.