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Can this project support num-beams in opus-mt model ? #1
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Yes, beam search is supported, by setting the By default, it uses a beam size of 5. Accuracy measurements are on the way: I first need to create a good test set, on which the models were not trained. And then find a way to present the results in an efficient way. |
I find some framework provide lexicon validation on different beam search conclusion |
Is this implemented in huggingface transformers? Then I could add it. I currently have no direct plan to add this feature. But pull requests adding this feature would be welcome :) |
I think sockeye’s N-best translations(use reranker) and Lexical constraints may help with above discussion. |
All the options that huggingface is providing for the generate method can now be passed to the translate method (in the recent v1.1.0 release). |
I find similar project called ktrain support this.
located in
https://github.com/amaiya/ktrain/blob/5c9c6b333115be44433639c4bc4c091bd79ab65c/ktrain/text/translation/core.py
and have some accuracy measurement output to summarize the conclusion will more interesting.
Can multilingual sentence embedding can do some help ?
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