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michaelfeil/
ct2fast-opus-mt-fr-en

Name: ct2fast-opus-mt-fr-en
Availability: InStock

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# Fast-Inference with Ctranslate2

Speedup inference by 2x-8x using int8 inference in C++

quantized version of Helsinki-NLP/opus-mt-fr-en

pip install hf-hub-ctranslate2>=1.0.0 ctranslate2>=3.13.0

Converted using

ct2-transformers-converter --model Helsinki-NLP/opus-mt-fr-en --output_dir /home/michael/tmp-ct2fast-opus-mt-fr-en --force --copy_files README.md generation_config.json tokenizer_config.json vocab.json source.spm .gitattributes target.spm --quantization float16

Checkpoint compatible to ctranslate2 and hf-hub-ctranslate2

compute_type=int8_float16 for device="cuda"
compute_type=int8 for device="cpu"

python

from hf_hub_ctranslate2 import TranslatorCT2fromHfHub, GeneratorCT2fromHfHub
from transformers import AutoTokenizer

model_name = "michaelfeil/ct2fast-opus-mt-fr-en"
# use either TranslatorCT2fromHfHub or GeneratorCT2fromHfHub here, depending on model.
model = TranslatorCT2fromHfHub(
        # load in int8 on CUDA
        model_name_or_path=model_name, 
        device="cuda",
        compute_type="int8_float16",
        tokenizer=AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fr-en")
)
outputs = model.generate(
    text=["How do you call a fast Flan-ingo?", "User: How are you doing?"],
)
print(outputs)

Licence and other remarks:

This is just a quantized version. Licence conditions are intended to be idential to original huggingface repo.

Original description

opus-mt-fr-en

source languages: fr
target languages: en
OPUS readme: fr-en
dataset: opus
model: transformer-align
pre-processing: normalization + SentencePiece
download original weights: opus-2020-02-26.zip
test set translations: opus-2020-02-26.test.txt
test set scores: opus-2020-02-26.eval.txt

Benchmarks

testset	BLEU	chr-F
newsdiscussdev2015-enfr.fr.en	33.1	0.580
newsdiscusstest2015-enfr.fr.en	38.7	0.614
newssyscomb2009.fr.en	30.3	0.569
news-test2008.fr.en	26.2	0.542
newstest2009.fr.en	30.2	0.570
newstest2010.fr.en	32.2	0.590
newstest2011.fr.en	33.0	0.597
newstest2012.fr.en	32.8	0.591
newstest2013.fr.en	33.9	0.591
newstest2014-fren.fr.en	37.8	0.633
Tatoeba.fr.en	57.5	0.720