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A timestep-embedding vector, which indicates to the backbone about how much noise there is in the image. For example, an embedding of timestep t = 0 {\displaystyle t=0} would indicate that the input image is already noiseless, while t = 100 {\displaystyle t=100} would indicate a large amount of noise.
Hugging Face, Inc. is an American company incorporated under the Delaware General Corporation Law [1] and based in New York City that develops computation tools for building applications using machine learning.
LangChain was launched in October 2022 as an open source project by Harrison Chase, while working at machine learning startup Robust Intelligence. The project quickly garnered popularity, [3] with improvements from hundreds of contributors on GitHub, trending discussions on Twitter, lively activity on the project's Discord server, many YouTube tutorials, and meetups in San Francisco and London.
Features of each instance such as class, class size, and instructor are given. 151 Text Classification 1997 [18] [19] W. Loh et al. Vietnamese Students’ Feedback Corpus (UIT-VSFC) Students’ Feedback. Comments 16,000 Text Classification 1997 [20] Nguyen et al. Vietnamese Social Media Emotion Corpus (UIT-VSMEC) Users’ Facebook Comments ...
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]
This is an accepted version of this page This is the latest accepted revision, reviewed on 28 January 2025. Computer graphics images defined by points, lines and curves This article is about computer illustration. For other uses, see Vector graphics (disambiguation). Example showing comparison of vector graphics and raster graphics upon magnification Vector graphics are a form of computer ...
In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object. Many algorithms in machine learning require a numerical representation of objects, since such representations facilitate processing and statistical analysis.
A latent space, also known as a latent feature space or embedding space, is an embedding of a set of items within a manifold in which items resembling each other are positioned closer to one another.