michaelfeil/ct2fast-opus-mt-es-en

# 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

• —source group: Spanish
• —target group: English
• —OPUS readme: spa-eng

• —model: transformer
• —source language(s): spa
• —target language(s): eng
• —model: transformer
• —pre-processing: normalization + SentencePiece (spm32k,spm32k)
• —download original weights: opus-2020-08-18.zip
• —test set translations: opus-2020-08-18.test.txt
• —test set scores: opus-2020-08-18.eval.txt

Benchmarks

System Info:

• —hf_name: spa-eng

• —source_languages: spa

• —target_languages: eng

• —opusreadmeurl: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/spa-eng/README.md

• —original_repo: Tatoeba-Challenge

• —tags:
• —ctranslate2 ['translation']

• —languages: ['es', 'en']

• —src_constituents: {'spa'}

• —tgt_constituents: {'eng'}

• —src_multilingual: False

• —tgt_multilingual: False

• —prepro: normalization + SentencePiece (spm32k,spm32k)

• —url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/spa-eng/opus-2020-08-18.zip

• —urltestset: https://object.pouta.csc.fi/Tatoeba-MT-models/spa-eng/opus-2020-08-18.test.txt

• —src_alpha3: spa

• —tgt_alpha3: eng

• —short_pair: es-en

• —chrF2_score: 0.7390000000000001

• —bleu: 59.6

• —brevity_penalty: 0.9740000000000001

• —ref_len: 79376.0

• —src_name: Spanish

• —tgt_name: English

• —train_date: 2020-08-18 00:00:00

• —src_alpha2: es

• —tgt_alpha2: en

• —prefer_old: False

• —long_pair: spa-eng

• —helsinkigitsha: d2f0910c89026c34a44e331e785dec1e0faa7b82

• —transformersgitsha: f7af09b4524b784d67ae8526f0e2fcc6f5ed0de9

• —port_machine: brutasse

• —port_time: 2020-08-24-18:20