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--- |
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tags: |
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- ctranslate2 |
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- translation |
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license: apache-2.0 |
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--- |
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# # Fast-Inference with Ctranslate2 |
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Speedup inference by 2x-8x using int8 inference in C++ |
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quantized version of [Helsinki-NLP/opus-mt-ROMANCE-en](https://huggingface.co/Helsinki-NLP/opus-mt-ROMANCE-en) |
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```bash |
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pip install hf-hub-ctranslate2>=1.0.0 ctranslate2>=3.13.0 |
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``` |
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Converted using |
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``` |
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ct2-transformers-converter --model Helsinki-NLP/opus-mt-ROMANCE-en --output_dir /home/michael/tmp-ct2fast-opus-mt-ROMANCE-en --force --copy_files README.md generation_config.json tokenizer_config.json vocab.json source.spm .gitattributes target.spm --quantization float16 |
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``` |
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Checkpoint compatible to [ctranslate2](https://github.com/OpenNMT/CTranslate2) and [hf-hub-ctranslate2](https://github.com/michaelfeil/hf-hub-ctranslate2) |
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- `compute_type=int8_float16` for `device="cuda"` |
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- `compute_type=int8` for `device="cpu"` |
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```python |
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from hf_hub_ctranslate2 import TranslatorCT2fromHfHub, GeneratorCT2fromHfHub |
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from transformers import AutoTokenizer |
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model_name = "michaelfeil/ct2fast-opus-mt-ROMANCE-en" |
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# use either TranslatorCT2fromHfHub or GeneratorCT2fromHfHub here, depending on model. |
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model = TranslatorCT2fromHfHub( |
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# load in int8 on CUDA |
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model_name_or_path=model_name, |
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device="cuda", |
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compute_type="int8_float16", |
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tokenizer=AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ROMANCE-en") |
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) |
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outputs = model.generate( |
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text=["How do you call a fast Flan-ingo?", "User: How are you doing?"], |
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) |
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print(outputs) |
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``` |
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# Licence and other remarks: |
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This is just a quantized version. Licence conditions are intended to be idential to original huggingface repo. |
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# Original description |
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### opus-mt-ROMANCE-en |
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* source languages: fr,fr_BE,fr_CA,fr_FR,wa,frp,oc,ca,rm,lld,fur,lij,lmo,es,es_AR,es_CL,es_CO,es_CR,es_DO,es_EC,es_ES,es_GT,es_HN,es_MX,es_NI,es_PA,es_PE,es_PR,es_SV,es_UY,es_VE,pt,pt_br,pt_BR,pt_PT,gl,lad,an,mwl,it,it_IT,co,nap,scn,vec,sc,ro,la |
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* target languages: en |
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* OPUS readme: [fr+fr_BE+fr_CA+fr_FR+wa+frp+oc+ca+rm+lld+fur+lij+lmo+es+es_AR+es_CL+es_CO+es_CR+es_DO+es_EC+es_ES+es_GT+es_HN+es_MX+es_NI+es_PA+es_PE+es_PR+es_SV+es_UY+es_VE+pt+pt_br+pt_BR+pt_PT+gl+lad+an+mwl+it+it_IT+co+nap+scn+vec+sc+ro+la-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/fr+fr_BE+fr_CA+fr_FR+wa+frp+oc+ca+rm+lld+fur+lij+lmo+es+es_AR+es_CL+es_CO+es_CR+es_DO+es_EC+es_ES+es_GT+es_HN+es_MX+es_NI+es_PA+es_PE+es_PR+es_SV+es_UY+es_VE+pt+pt_br+pt_BR+pt_PT+gl+lad+an+mwl+it+it_IT+co+nap+scn+vec+sc+ro+la-en/README.md) |
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* dataset: opus |
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* model: transformer |
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* pre-processing: normalization + SentencePiece |
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* download original weights: [opus-2020-04-01.zip](https://object.pouta.csc.fi/OPUS-MT-models/fr+fr_BE+fr_CA+fr_FR+wa+frp+oc+ca+rm+lld+fur+lij+lmo+es+es_AR+es_CL+es_CO+es_CR+es_DO+es_EC+es_ES+es_GT+es_HN+es_MX+es_NI+es_PA+es_PE+es_PR+es_SV+es_UY+es_VE+pt+pt_br+pt_BR+pt_PT+gl+lad+an+mwl+it+it_IT+co+nap+scn+vec+sc+ro+la-en/opus-2020-04-01.zip) |
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* test set translations: [opus-2020-04-01.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/fr+fr_BE+fr_CA+fr_FR+wa+frp+oc+ca+rm+lld+fur+lij+lmo+es+es_AR+es_CL+es_CO+es_CR+es_DO+es_EC+es_ES+es_GT+es_HN+es_MX+es_NI+es_PA+es_PE+es_PR+es_SV+es_UY+es_VE+pt+pt_br+pt_BR+pt_PT+gl+lad+an+mwl+it+it_IT+co+nap+scn+vec+sc+ro+la-en/opus-2020-04-01.test.txt) |
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* test set scores: [opus-2020-04-01.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/fr+fr_BE+fr_CA+fr_FR+wa+frp+oc+ca+rm+lld+fur+lij+lmo+es+es_AR+es_CL+es_CO+es_CR+es_DO+es_EC+es_ES+es_GT+es_HN+es_MX+es_NI+es_PA+es_PE+es_PR+es_SV+es_UY+es_VE+pt+pt_br+pt_BR+pt_PT+gl+lad+an+mwl+it+it_IT+co+nap+scn+vec+sc+ro+la-en/opus-2020-04-01.eval.txt) |
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## Benchmarks |
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| testset | BLEU | chr-F | |
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|-----------------------|-------|-------| |
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| Tatoeba.fr.en | 62.2 | 0.750 | |
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