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Hugging Face, Inc. is a Franco-American company that develops computation tools for building applications using machine learning. It is known for its transformers library built for natural language processing applications.
Toggle Missing formula functions subsection. ... 4 Allow sorting tables via calculator widgets. ... Template talk: Calculator/feature requests.
Add a calculator widget to the page. Like a spreadsheet you can refer to other widgets in the same page. Template parameters [Edit template data] Parameter Description Type Status id id The id for this input. This is used to reference it in formula of other calculator templates String required type type What type of input box Suggested values plain number text radio checkbox passthru hidden ...
For further details check the project's GitHub repository or the Hugging Face dataset cards (taskmaster-1, taskmaster-2, taskmaster-3). Dialog/Instruction prompted 2019 [339] Byrne and Krishnamoorthi et al. DrRepair A labeled dataset for program repair. Pre-processed data Check format details in the project's worksheet. Dialog/Instruction prompted
Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
Probability generating functions are particularly useful for dealing with functions of independent random variables. For example: If , =,,, is a sequence of independent (and not necessarily identically distributed) random variables that take on natural-number values, and
With an additional (free) package, it's also possible to generate SVG-graphs with R directly. See an example with code on Image:Circle area Monte Carlo integration2.svg. Other packages (lattice, ggplot2) provide alternative graphics facilities or syntax. Here is another example with data.
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]