How to train an MT (OPUS-CAT)?

Hi folks,
Does anybody know a resource (text or video) that explains how to train the OPUS-CAT MT engine (by ) with my TMs? 
And also, does the term 'fine-tuning' means the same as 'training/learning' in terms of MT? I disocvered OPUS-CAT MT engine incidentally and it looks very interesting to me. Even out of the box (not trained yet), it translates from English into Russian not worse than DeepL. But unlike DeepL, it is trainable, though I have no idea how to train it. Is it sufficient just to use this MT along with my TMs in my translation jobs, or should I take some specific steps for this purpose? Any tip?

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  • The fine-tuning functionality is meant more as a preprocessing step before starting work a project. The workflow I had in mind when I designed was as follows:

    1. You receive a translation job with existing translations or a useful TM (project-specific translations).
    2. You initiate the fine-tuning of the base model in OPUS-CAT MT Engine with the project-specific translations using the batch task.
    3. Wait an hour or so for the fine-tuning to complete.
    4. When the fine-tuning is complete, select the fine-tuned model in the OPUS-CAT plugin (by selecting its model tag) and start on the project.

    The fine-tuning is ideally suited for large-scale projects that have a lot of existing translations. The fine-tuning will usually pick up the terminology and sentence structures used in the existing translations, which makes the MT much more useful (depends on the project, though).

    It might also be useful to train a fine-tuned model for a specific client, and then use this model for all jobs for this client. This would be easiest to do with the TMX fine-tuning in the engine.

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