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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 ]
Hugging Face, Inc. is an American company that develops computation tools for building applications using machine learning. It is incorporated under the Delaware General Corporation Law [ 1 ] and based in New York City .
Multimodal sentiment analysis is a technology for traditional text-based sentiment analysis, which includes modalities such as audio and visual data. [1] It can be bimodal, which includes different combinations of two modalities, or trimodal, which incorporates three modalities. [ 2 ]
The cloud computing arm of Alphabet Inc said on Thursday it had formed a partnership with startup Hugging Face to ease artificial intelligence (AI) software development in the company's Google Cloud.
Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.
In the project life cycle context, a 6D model is usually delivered to the owner when a construction project is finished. The "As-Built" BIM model is populated with relevant building component information such as product data and details, maintenance/operation manuals, cut sheet specifications, photos, warranty data, web links to product online ...
A model is usually built for a most probable (or base) case. Then, a model sensitivity analysis is conducted to determine effects of changes in input variables on key outputs, such as internal rate of return (IRR), net present value (NPV) and payback period. For discussion (a) re cash-flow modelling, see Valuation using discounted cash flows ...
The DICE framework, or Duration, Integrity, Commitment, and Effort framework is a tool for evaluating projects, [1] predicting project outcomes, and allocating resources strategically to maximize delivery of a program or portfolio of initiatives, aiming for consistency in evaluating projects with subjective inputs.