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michaelfeil
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ct2fast-opus-mt-es-en

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ctranslate2
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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-es-en

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

Converted using

ct2-transformers-converter --model Helsinki-NLP/opus-mt-es-en --output_dir /home/michael/tmp-ct2fast-opus-mt-es-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"
from hf_hub_ctranslate2 import TranslatorCT2fromHfHub, GeneratorCT2fromHfHub
from transformers import AutoTokenizer

model_name = "michaelfeil/ct2fast-opus-mt-es-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-es-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

spa-eng

Benchmarks

testset BLEU chr-F
newssyscomb2009-spaeng.spa.eng 30.6 0.570
news-test2008-spaeng.spa.eng 27.9 0.553
newstest2009-spaeng.spa.eng 30.4 0.572
newstest2010-spaeng.spa.eng 36.1 0.614
newstest2011-spaeng.spa.eng 34.2 0.599
newstest2012-spaeng.spa.eng 37.9 0.624
newstest2013-spaeng.spa.eng 35.3 0.609
Tatoeba-test.spa.eng 59.6 0.739

System Info:

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