Instructions to use medodeyaa/dentor-helsinki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use medodeyaa/dentor-helsinki 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="medodeyaa/dentor-helsinki")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("medodeyaa/dentor-helsinki") model = AutoModelForSeq2SeqLM.from_pretrained("medodeyaa/dentor-helsinki", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - en | |
| - ar | |
| license: apache-2.0 | |
| library_name: transformers | |
| pipeline_tag: translation | |
| tags: | |
| - marian | |
| - translation | |
| inference: true | |
| widget: | |
| - text: "The patient has periapical abscess and requires root canal treatment." | |
| ### eng-ara | |
| * source group: English | |
| * target group: Arabic | |
| * OPUS readme: [eng-ara](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-ara/README.md) | |
| * model: transformer | |
| * source language(s): eng | |
| * target language(s): acm afb apc apc_Latn ara ara_Latn arq arq_Latn ary arz | |
| * 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: [opus-2020-07-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ara/opus-2020-07-03.zip) | |
| * test set translations: [opus-2020-07-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ara/opus-2020-07-03.test.txt) | |
| * test set scores: [opus-2020-07-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ara/opus-2020-07-03.eval.txt) | |
| ## Benchmarks | |
| | testset | BLEU | chr-F | | |
| |-----------------------|-------|-------| | |
| | Tatoeba-test.eng.ara | 14.0 | 0.437 | | |
| ### System Info: | |
| - hf_name: eng-ara | |
| - source_languages: eng | |
| - target_languages: ara | |
| - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-ara/README.md | |
| - original_repo: Tatoeba-Challenge | |
| - tags: ['translation'] | |
| - languages: ['en', 'ar'] | |
| - src_constituents: {'eng'} | |
| - tgt_constituents: {'apc', 'ara', 'arq_Latn', 'arq', 'afb', 'ara_Latn', 'apc_Latn', 'arz'} | |
| - src_multilingual: False | |
| - tgt_multilingual: False | |
| - prepro: normalization + SentencePiece (spm32k,spm32k) | |
| - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ara/opus-2020-07-03.zip | |
| - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ara/opus-2020-07-03.test.txt | |
| - src_alpha3: eng | |
| - tgt_alpha3: ara | |
| - short_pair: en-ar | |
| - chrF2_score: 0.43700000000000006 | |
| - bleu: 14.0 | |
| - brevity_penalty: 1.0 | |
| - ref_len: 58935.0 | |
| - src_name: English | |
| - tgt_name: Arabic | |
| - train_date: 2020-07-03 | |
| - src_alpha2: en | |
| - tgt_alpha2: ar | |
| - prefer_old: False | |
| - long_pair: eng-ara | |
| - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 | |
| - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b | |
| - port_machine: brutasse | |
| - port_time: 2020-08-21-14:41 |