We used the
OpusDistillery
to train new a new student with the tiny architecture, with a regular transformer decoder.
For training data, we used
Tatoeba
.
The configuration file fed into OpusDistillery can be found
here
.
How to run
from transformers import MarianMTModel, MarianTokenizer
model_name = "Helsinki-NLP/opus-mt_tiny_eng-tur"
tokenizer = MarianTokenizer.from_pretrained(model_name)
model = MarianMTModel.from_pretrained(model_name)
tok = tokenizer("Persians have a relatively easy and mostly smooth grammar.", return_tensors="pt").input_ids
output = model.generate(tok)[0]
tokenizer.decode(output, skip_special_tokens=True)
Benchmarks
Teacher
testset
BLEU
chr-F
COMET
Flores+
31.4
62.8
0.8854
Bouquet
36.6
66.5
0.9058
Student
testset
BLEU
chr-F
COMET
Flores+
28.5
62.8
0.8633
Bouquet
33.0
64.6
0.8899
Marian models
We also provide Marian-compatible versions of this model. To use them, compile
Marian
and run decoding with
marian-decoder
, for example:
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