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LangChain is a software framework that helps facilitate the integration of large language models (LLMs) into applications. As a language model integration framework, LangChain's use-cases largely overlap with those of language models in general, including document analysis and summarization , chatbots , and code analysis .
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. [24] In-context learning is an emergent ability [25] of large language models.
One-shot learning is an object categorization problem, found mostly in computer vision. Whereas most machine learning -based object categorization algorithms require training on hundreds or thousands of examples, one-shot learning aims to classify objects from one, or only a few, examples.
Videos. Video search results are videos that are sorted by relevance of the video in the descending order. A number of factors are considered when determining whether a video is relevant to your search request. Since these methods are not entirely foolproof, it is possible some inappropriate videos may be included in the list that you see. Maps
Specifically, to count as a legitimate view, a user must intentionally initiate the playback of the video and play at least 30 seconds of the video (or the entire video for shorter videos). Additionally, while replays count as views, there is a limit of 4 or 5 views per IP address during a 24-hour period, after which point, no further views ...
YouTube Shorts, created in 2020, is the short-form section of the online video-sharing platform YouTube.. YouTube Shorts focuses on vertical videos that are of less than 180 seconds duration, and has various features for user interaction.
One-shot learning (computer vision) Topics referred to by the same term This disambiguation page lists articles associated with the title Few-shot learning .
The main use of these search engines is the increasing creation of audiovisual content and the need to manage it properly. The digitization of audiovisual archives and the establishment of the Internet, has led to large quantities of video files stored in big databases, whose recovery can be very difficult because of the huge volumes of data and the existence of a semantic gap.