# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Rahulrr/language_model_en_he")
model = AutoModelForSeq2SeqLM.from_pretrained("Rahulrr/language_model_en_he")Quick Links
en-he
source group: English
target group: Hebrew
OPUS readme: eng-heb
model: transformer-align
source language(s): eng
target language(s): heb
model: transformer-align
pre-processing: normalization + SentencePiece (spm32k,spm32k)
download original weights: opus+bt-2021-04-13.zip
test set translations: opus+bt-2021-04-13.test.txt
test set scores: opus+bt-2021-04-13.eval.txt
Benchmarks
| testset | BLEU | chr-F | #sent | #words | BP |
|---|---|---|---|---|---|
| Tatoeba-test.eng-heb | 37.8 | 0.601 | 10000 | 60359 | 1.000 |
System Info:
- hf_name: en-he
- source_languages: eng
- target_languages: heb
- opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-heb/README.md
- original_repo: Tatoeba-Challenge
- tags: ['translation']
- languages: ['en', 'he']
- src_constituents: ('English', {'eng'})
- tgt_constituents: ('Hebrew', {'heb'})
- src_multilingual: False
- tgt_multilingual: False
- long_pair: eng-heb
- prepro: normalization + SentencePiece (spm32k,spm32k)
- url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-heb/opus+bt-2021-04-13.zip
- url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-heb/opus+bt-2021-04-13.test.txt
- src_alpha3: eng
- tgt_alpha3: heb
- chrF2_score: 0.601
- bleu: 37.8
- src_name: English
- tgt_name: Hebrew
- train_date: 2021-04-13 00:00:00
- src_alpha2: en
- tgt_alpha2: he
- prefer_old: False
- short_pair: en-he
- helsinki_git_sha: c4e978d8de47875b482653b423dcfe968979d7d5
- transformers_git_sha: 56b83cf049823ed074a655eceb28f31e2077c6eb
- port_machine: LAPIN4GLQ2G3
- port_time: 2022-06-22-19:47
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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="Rahulrr/language_model_en_he")