Comments (3)
The scripts are still very much hard-coded to our computing environment. I'll try to make them more generic and generally useful as soon as possible. Stay tuned .... OpusTools can definitely be used for retrieving the data. I didn't use opus_express to make the data sets but that would actually be a good way of doing it. So far, I rely on local copies of OPUS that I can retrieve quickly. I can tell you that I also work an improved way of handling language codes and the variation that you can find in OPUS This causes quite some confusion and I hope to improve the situation in some future release.
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Can we use the dataset from https://github.com/Helsinki-NLP/Tatoeba-Challenge ?
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Now the scripts support fetching the data directly from OPUS. The opus-tools python package needs to be installed. Using data from the Tatoeba-Challenge can easily be used by adding the suffix -tatoeba
to the build targets. See this for more info: https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/doc/TatoebaChallenge.md
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Related Issues (20)
- No Latin models?
- Decode target & source smp
- How to translate from english to Japan?
- Using OPUS-MT with DeepSpeed
- update Dockerfile.gpu--fixed
- different sizes of dictionaries in different models HOT 1
- Reproduced crash on Opus-mt-en-de model using string "J" and "J-10" HOT 1
- Unable to find current origin/master revision in submodule path HOT 2
- Hyperparameters used for pretrained models? HOT 1
- how to train our dataset HOT 3
- Unbelievably High BLEU scores from finetuning... HOT 3
- Data for Brazilian Portuguese HOT 2
- Lack of transparency on used training data. - Does finetuning make sense? HOT 1
- preprocess.sh [: ==: unary operator expected HOT 2
- Fine-tuning with guided alignment
- Fine-tuning models using HuggingFace libraries
- opus-mt-tc-big-tr-en doesn't work properly.
- I want a ja-ko model.
- What's the prefix for "Helsinki-NLP/opus-mt-zh-en" when using "AutoModelForSeq2SeqLM"?
- New model
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