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High-quality cotton fiber paper is known to last hundreds of years without appreciable fading, discoloration, or deterioration, [1] so it is often used for important documents, such as the archival copies of dissertations or theses. As a rule of thumb, for each percentage point of cotton fiber, a user may expect one year of resisting ...
The toothiness allows the paper to take charcoal easily and evenly. Ingres paper is favored in book arts for its antique appearance and pH neutrality. Prominent manufactures include Canson, Hahnemühle (sometimes called "German Ingres"), and Fabriano. Ingres paper has a high rag content (around 65%) and is gelatin sized. It is available in a ...
Original file (2,268 × 3,000 pixels, file size: 8.08 MB, MIME type: application/pdf, 6 pages) This is a file from the Wikimedia Commons . Information from its description page there is shown below.
The 1911 Encyclopædia Britannica boasted of its India paper printing. India paper is a type of paper which from 1875 has been based on bleached hemp and rag fibres, that produced a very thin, tough opaque white paper. It has a basis weight of 20 pounds (30 g/m 2; typical office paper is 80 g/m 2), yet bulks 1,000 pages to the inch (390 per ...
[citation needed] A4 ("metric") paper is easier to obtain in the US than US letter can be had elsewhere. [citation needed]. The ISO 216:2007 is the current international standard for paper sizes, including writing papers and some types of printing papers. This standard describes the paper sizes under what the ISO calls the A, B, and C series ...
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[1] [2] The image of the written text may be sensed "off line" from a piece of paper by optical scanning (optical character recognition) or intelligent word recognition. Alternatively, the movements of the pen tip may be sensed "on line", for example by a pen-based computer screen surface, a generally easier task as there are more clues available.
In-context learning, refers to a model's ability to temporarily learn from prompts.For example, a prompt may include a few examples for a model to learn from, such as asking the model to complete "maison → house, chat → cat, chien →" (the expected response being dog), [23] an approach called few-shot learning.