![]() To use the YouTube Video Editor, you must sign into your YouTube (or Google) account. The YouTube Video Editor is one such tool. While there are many excellent standalone applications out there, there are also some useful online tools that you can use to make your video stand out from the crowd. To start with, if you are interested in customizing and enhancing your own video (or any video, for that matter), you will need to use a video editor. We’ll also show you how to add annotations to your YouTube videos (annotations are those little info bubbles we’ve all seen on YouTube videos). In this article we will look at some excellent YouTube resources that you may not be aware of, including an online video editor provided by YouTube. Those restrictions do not apply when using Spark NLP models and embeddings.If you’ve read our tutorial on how to add a YouTube video to your website, you may be interested in customizing your own videos on YouTube. In this case, the pre-annotation server has to be deleted first, and then the training can be started. Since one floating license can only be used for one server, it is not possible to deploy a pre-annotation server and then trigger training from the same project when only one license is available. For example, to deploy 5 pre-annotation servers using Spark NLP for Healthcare models or embeddings, across 5 different projects, you will need 5 floating licenses. ![]() ![]() The number of available floating licenses can influence the creation of multiple training and pre-annotation servers. Once the form is submitted, a validation link is sent to the provided email address, and the trial license is automatically imported to the NLP Lab when the link is clicked, making it readily available for use. To obtain a trial license, users are required to fill out the form on the “Get License” tab, providing their organizational email. This enhanced workflow incorporates a new “Get License” tab, while maintaining the status quo of the Import License and Existing Licenses tabs. This updated design enables users to initiate a trial license request directly from the License page, thereby eliminating the need for external page navigation. Version 4.10 offers an updated License page layout that streamlines the process of obtaining a trial license. Mixing floating and air-gapped licenses on the same Annotation Lab instance is not allowed. To run multiple model training jobs and/or pre-annotations servers, users must provide multiple floating licenses.Īnnotation Lab supports either floating licenses or air-gapped licenses. One floating license is bound to only one server (pre-annotation server, OCR server, training job) at a time. Licenses are a must for training Healthcare, Finance, and Legal models and deploying these models as pre-annotation servers.įloating licenses can be acquired on self-service via my. Depending on the scope of the available license, users can perform model training and/or deploy pre-annotation servers. The License page shows the history of license uploads with detailed information like License Info, Status, Renewal Date, and License Secrets.Īnnotation Lab supports floating licenses with different scopes ( ocr: training, ocr: inference, healthcare: inference, healthcare: training, finance: inference, finance: training, legal: inference, legal: training). Once a valid license is uploaded, all the licensed (Healthcare, Finance, Legal, and Visual NLP) models and embeddings become available for download. The license is generated by the John Snow Labs license server and is available on my. The admin user can upload a Spark NLP license JSON file by visiting the License page. Access to training custom models using licensed embeddings. ![]() Access to healthcare, finance, and legal embeddings.Access to licensed models for pre-annotation.pre-trained models and embeddings) admin user can import a license (Healthcare, Finance, Legal, or Visual NLP) which will activate additional features: To gain access to licensed resources (e.g. Those are available on the Models Hub page. By default, the Annotation Lab allows access to community pre-trained models and embeddings. ![]()
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