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The typical training time for domain-adapted engines is between 10 and 28 hours.
AI-boosted engines
AI-boosted engines Boosted Engines are available from Globalese V5. AI boosted These engines are trained based on domain-adapted engines. They are , combining the terminology and style accuracy of a domain-adapted engine with the linguistic capabilities of large language models. In Globalese V5, AI-Boosted Engines use currently GPT models from OpenAI.
Use case
AI-boosted engines are using typically provide the best results in most cases. They are especially effective if the engine is not designed exclusively for a very specific domain, such as the translation of a technical documentation. However, the results may vary, as GPT models from OpenAI are non-deterministic by default.
Required training data
Same as for the domain-adapted engines.
Typical training time
The typical training time for domain-adapted engines is between 10 and 28 hours.
Additional information
Please note that GPT models from OpenAI are currently available as a beta service.
Stock+ engines
Stock+ engines are customized stock engines, i.e. engines trained by extending a pre-trained stock engine with you own master data. The selected master data will be part of the engine. If there is new content in the master corpora, the engine will learn it. However, you should not expect changes in terminology and style preferences in the engine based on the master data added.
Use case
The typical use case for stock+ engines is where it is important to use a generic engine trained on a large data set, which is however incorporating your own training data too. You can also use this option if you the size of your own training data is not enough to train a domain-adapted engine. Some examples: annual reports, user generated content, web pages.
Required training data
A minimum of 1,000 segments, and a maximum of 1,000,000.
Typical training time
The typical training time for stock+ engines is between 10 minutes to 4 hours.
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