Re: [Moses-support] Conversion of phrase model to PhraseDictionaryCompact

maybe try -encoding None On 08/12/2016 19:44, Shubham Khandelwal wrote: Hi Hieu, Thanks for your reply. Yes, I have used the absolute path and also I tried with -T but it did not work. Is there any other solution to this problem. Btw, Can anybody please upload the compact model of all

Re: [Moses-support] Conversion of phrase model to PhraseDictionaryCompact

Hi Hieu, Thanks for your reply. Yes, I have used the absolute path and also I tried with -T but it did not work. Is there any other solution to this problem. Btw, Can anybody please upload the compact model of all pre-made models as this will take less space and also it will be very fast during

Re: [Moses-support] Conversion of phrase model to PhraseDictionaryCompact

the previous email you referred to says that the directory * binarised-model/* *must exist before you run it, otherwise it will segfault. I would also use absolute path to make sure, ie. not * *binarised-model/phrase-table * *but* * /home/shubham/moses/binarised-model/phrase-table * *The

Re: [Moses-support] RNN-based features in Moses

Hello Hakimeh, the branch https://github.com/moses-smt/mosesdecoder/tree/nmt-hybrid supports NMT (which is basically an RNN conditioned on the source text) as a feature function in Moses. It is described in this paper: @inproceedings{junczysdowmunt-dwojak-sennrich:2016:WMT, address =

Re: [Moses-support] Conversion of phrase model to PhraseDictionaryCompact

Hello, This is just the reminder of my previous email. Thanking You. Regards, Shubham On Thu, Dec 8, 2016 at 9:04 AM, Shubham Khandelwal wrote: > Hello, > > I have just downloaded phrase-table.2.gz (18GB) de-en model > and phrase-table.3.gz (22GB) fr-en model from the

[Moses-support] RNN-based features in Moses

Dear Moses Community, I'm searching for some RNN-based features added to Moses decoder or used in reranking Moses' n-best list. It seems Moses have some (LM) features based on Feedforward neural networks but I haven't find any implementation for recurrent neural networks in Moses. Apparently