Instructions to use Helsinki-NLP/opus-mt-en-phi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-phi with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-en-phi")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-phi") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-phi") - Notebooks
- Google Colab
- Kaggle
eng-phi
source group: English
target group: Philippine languages
OPUS readme: eng-phi
model: transformer
source language(s): eng
target language(s): akl_Latn ceb hil ilo pag war
model: transformer
pre-processing: normalization + SentencePiece (spm32k,spm32k)
a sentence initial language token is required in the form of
>>id<<(id = valid target language ID)download original weights: opus2m-2020-08-01.zip
test set translations: opus2m-2020-08-01.test.txt
test set scores: opus2m-2020-08-01.eval.txt
Benchmarks
| testset | BLEU | chr-F |
|---|---|---|
| Tatoeba-test.eng-akl.eng.akl | 7.1 | 0.245 |
| Tatoeba-test.eng-ceb.eng.ceb | 10.5 | 0.435 |
| Tatoeba-test.eng-hil.eng.hil | 18.0 | 0.506 |
| Tatoeba-test.eng-ilo.eng.ilo | 33.4 | 0.590 |
| Tatoeba-test.eng.multi | 13.1 | 0.392 |
| Tatoeba-test.eng-pag.eng.pag | 19.4 | 0.481 |
| Tatoeba-test.eng-war.eng.war | 12.8 | 0.441 |
System Info:
hf_name: eng-phi
source_languages: eng
target_languages: phi
opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-phi/README.md
original_repo: Tatoeba-Challenge
tags: ['translation']
languages: ['en', 'phi']
src_constituents: {'eng'}
tgt_constituents: {'ilo', 'akl_Latn', 'war', 'hil', 'pag', 'ceb'}
src_multilingual: False
tgt_multilingual: True
prepro: normalization + SentencePiece (spm32k,spm32k)
url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-phi/opus2m-2020-08-01.zip
url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-phi/opus2m-2020-08-01.test.txt
src_alpha3: eng
tgt_alpha3: phi
short_pair: en-phi
chrF2_score: 0.392
bleu: 13.1
brevity_penalty: 1.0
ref_len: 30022.0
src_name: English
tgt_name: Philippine languages
train_date: 2020-08-01
src_alpha2: en
tgt_alpha2: phi
prefer_old: False
long_pair: eng-phi
helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
port_machine: brutasse
port_time: 2020-08-21-14:41
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