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DBRX is an open-sourced large language model (LLM) developed by Mosaic ML team at Databricks, released on March 27, 2024. [ 1 ] [ 2 ] [ 3 ] It is a mixture-of-experts transformer model, with 132 billion parameters in total. 36 billion parameters (4 out of 16 experts) are active for each token. [ 4 ]
The Hugging Face Hub is a platform (centralized web service) for hosting: [20] Git-based code repositories, including discussions and pull requests for projects. models, also with Git-based version control; datasets, mainly in text, images, and audio;
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It is a general-purpose learner and its ability to perform the various tasks was a consequence of its general ability to accurately predict the next item in a sequence, [2] [7] which enabled it to translate texts, answer questions about a topic from a text, summarize passages from a larger text, [7] and generate text output on a level sometimes ...
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
Refdesk - free and family-friendly web site that indexes and reviews quality, credible, and current web-based resources; DeepDyve - big archive of literary and scholarly journal articles; free five-minute full-text previews.
xAI was founded by Musk [8] [9] [10] in Nevada [5] on March 9, 2023, and has since been headquartered in the San Francisco Bay Area in California. [11] Igor Babuschkin, formerly associated with Google's DeepMind unit, was recruited by Musk to be Chief Engineer.
Retrieval-augmented generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.