Closed remotejob closed 4 years ago
The MT models are not trained for replying to messages but rather to produce the same meaning covered by the input in some output message. Typically this is done for different languages but it can also be used in the same language for paraphrasing (or possibly error correction). I don't think it can be fine-tuned to do chat responses, this would rather require training from scratch I believe ...
I have about 1 mio chat pairs. How I can startup create model?
I guess you should have a look into general seq2seq models and train from scratch. I don't think that the OPUS-MT models are a good starting point.
My scope create Finnish language chat based on seq2seq model.
Can you give me some hits to start up. Create own model from scratch or fine tuning pre trained model? Particularly interesting https://huggingface.co/Helsinki-NLP/opus-mt-fi-fi model Maybe it possible to make fine tuning using Finnish language chat pairs
Kuka sei? /t Mina Alex ................................
Any hints appreciated. Maybe exist ready made project?
In fact I use for now: https://medium.com/axel-springer-tech/headliner-easy-training-and-deployment-of-seq2seq-models-2a26508b4dae https://github.com/as-ideas/headliner
Thanks.