# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-cau-en")
model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-cau-en", device_map="auto")cau-eng
source group: Caucasian languages
target group: English
OPUS readme: cau-eng
model: transformer
source language(s): abk ady che kat
target language(s): eng
model: transformer
pre-processing: normalization + SentencePiece (spm32k,spm32k)
download original weights: opus2m-2020-07-31.zip
test set translations: opus2m-2020-07-31.test.txt
test set scores: opus2m-2020-07-31.eval.txt
Benchmarks
| testset | BLEU | chr-F |
|---|---|---|
| Tatoeba-test.abk-eng.abk.eng | 0.3 | 0.134 |
| Tatoeba-test.ady-eng.ady.eng | 0.4 | 0.104 |
| Tatoeba-test.che-eng.che.eng | 0.6 | 0.128 |
| Tatoeba-test.kat-eng.kat.eng | 18.6 | 0.366 |
| Tatoeba-test.multi.eng | 16.6 | 0.351 |
System Info:
hf_name: cau-eng
source_languages: cau
target_languages: eng
opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/cau-eng/README.md
original_repo: Tatoeba-Challenge
tags: ['translation']
languages: ['ab', 'ka', 'ce', 'cau', 'en']
src_constituents: {'abk', 'kat', 'che', 'ady'}
tgt_constituents: {'eng'}
src_multilingual: True
tgt_multilingual: False
prepro: normalization + SentencePiece (spm32k,spm32k)
url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/cau-eng/opus2m-2020-07-31.zip
url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/cau-eng/opus2m-2020-07-31.test.txt
src_alpha3: cau
tgt_alpha3: eng
short_pair: cau-en
chrF2_score: 0.35100000000000003
bleu: 16.6
brevity_penalty: 1.0
ref_len: 6285.0
src_name: Caucasian languages
tgt_name: English
train_date: 2020-07-31
src_alpha2: cau
tgt_alpha2: en
prefer_old: False
long_pair: cau-eng
helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
port_machine: brutasse
port_time: 2020-08-21-14:41
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# 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-cau-en")