
### eng-sit

* source group: English 
* target group: Sino-Tibetan languages 
*  OPUS readme: [eng-sit](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-sit/README.md)

*  model: transformer
* source language(s): eng
* target language(s): bod brx brx_Latn cjy_Hans cjy_Hant cmn cmn_Hans cmn_Hant gan lzh lzh_Hans mya nan wuu yue yue_Hans yue_Hant zho zho_Hans zho_Hant
* 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](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-sit/opus2m-2020-08-01.zip)
* test set translations: [opus2m-2020-08-01.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-sit/opus2m-2020-08-01.test.txt)
* test set scores: [opus2m-2020-08-01.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-sit/opus2m-2020-08-01.eval.txt)

## Benchmarks

| testset               | BLEU  | chr-F |
|-----------------------|-------|-------|
| newsdev2017-enzh-engzho.eng.zho 	| 23.5 	| 0.217 |
| newstest2017-enzh-engzho.eng.zho 	| 23.2 	| 0.223 |
| newstest2018-enzh-engzho.eng.zho 	| 25.0 	| 0.230 |
| newstest2019-enzh-engzho.eng.zho 	| 20.2 	| 0.225 |
| Tatoeba-test.eng-bod.eng.bod 	| 0.4 	| 0.147 |
| Tatoeba-test.eng-brx.eng.brx 	| 0.5 	| 0.012 |
| Tatoeba-test.eng.multi 	| 25.7 	| 0.223 |
| Tatoeba-test.eng-mya.eng.mya 	| 0.2 	| 0.222 |
| Tatoeba-test.eng-zho.eng.zho 	| 29.2 	| 0.249 |


### System Info: 
- hf_name: eng-sit

- source_languages: eng

- target_languages: sit

- opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-sit/README.md

- original_repo: Tatoeba-Challenge

- tags: ['translation']

- languages: ['en', 'sit']

- src_constituents: {'eng'}

- tgt_constituents: set()

- src_multilingual: False

- tgt_multilingual: True

- prepro:  normalization + SentencePiece (spm32k,spm32k)

- url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-sit/opus2m-2020-08-01.zip

- url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/eng-sit/opus2m-2020-08-01.test.txt

- src_alpha3: eng

- tgt_alpha3: sit

- short_pair: en-sit

- chrF2_score: 0.223

- bleu: 25.7

- brevity_penalty: 0.907

- ref_len: 109538.0

- src_name: English

- tgt_name: Sino-Tibetan languages

- train_date: 2020-08-01

- src_alpha2: en

- tgt_alpha2: sit

- prefer_old: False

- long_pair: eng-sit

- helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

- transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

- port_machine: brutasse

- port_time: 2020-08-21-14:41
{"language": ["en", "sit"], "license": "apache-2.0", "tags": ["translation"]}
transformers pytorch tf marian text2text-generation translation en sit license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #en #sit #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 

### eng-sit


* source group: English
* target group: Sino-Tibetan languages
* OPUS readme: eng-sit
* model: transformer
* source language(s): eng
* target language(s): bod brx brx\_Latn cjy\_Hans cjy\_Hant cmn cmn\_Hans cmn\_Hant gan lzh lzh\_Hans mya nan wuu yue yue\_Hans yue\_Hant zho zho\_Hans zho\_Hant
* 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: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 23.5, chr-F: 0.217
testset: URL, BLEU: 23.2, chr-F: 0.223
testset: URL, BLEU: 25.0, chr-F: 0.230
testset: URL, BLEU: 20.2, chr-F: 0.225
testset: URL, BLEU: 0.4, chr-F: 0.147
testset: URL, BLEU: 0.5, chr-F: 0.012
testset: URL, BLEU: 25.7, chr-F: 0.223
testset: URL, BLEU: 0.2, chr-F: 0.222
testset: URL, BLEU: 29.2, chr-F: 0.249


### System Info:


* hf\_name: eng-sit
* source\_languages: eng
* target\_languages: sit
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'sit']
* src\_constituents: {'eng'}
* tgt\_constituents: set()
* src\_multilingual: False
* tgt\_multilingual: True
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: eng
* tgt\_alpha3: sit
* short\_pair: en-sit
* chrF2\_score: 0.223
* bleu: 25.7
* brevity\_penalty: 0.907
* ref\_len: 109538.0
* src\_name: English
* tgt\_name: Sino-Tibetan languages
* train\_date: 2020-08-01
* src\_alpha2: en
* tgt\_alpha2: sit
* prefer\_old: False
* long\_pair: eng-sit
* helsinki\_git\_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
* transformers\_git\_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
* port\_machine: brutasse
* port\_time: 2020-08-21-14:41



### eng-sit


* source group: English
* target group: Sino-Tibetan languages
* OPUS readme: eng-sit
* model: transformer
* source language(s): eng
* target language(s): bod brx brx\_Latn cjy\_Hans cjy\_Hant cmn cmn\_Hans cmn\_Hant gan lzh lzh\_Hans mya nan wuu yue yue\_Hans yue\_Hant zho zho\_Hans zho\_Hant
* 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: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 23.5, chr-F: 0.217
testset: URL, BLEU: 23.2, chr-F: 0.223
testset: URL, BLEU: 25.0, chr-F: 0.230
testset: URL, BLEU: 20.2, chr-F: 0.225
testset: URL, BLEU: 0.4, chr-F: 0.147
testset: URL, BLEU: 0.5, chr-F: 0.012
testset: URL, BLEU: 25.7, chr-F: 0.223
testset: URL, BLEU: 0.2, chr-F: 0.222
testset: URL, BLEU: 29.2, chr-F: 0.249 ### System Info:


* hf\_name: eng-sit
* source\_languages: eng
* target\_languages: sit
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'sit']
* src\_constituents: {'eng'}
* tgt\_constituents: set()
* src\_multilingual: False
* tgt\_multilingual: True
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: eng
* tgt\_alpha3: sit
* short\_pair: en-sit
* chrF2\_score: 0.223
* bleu: 25.7
* brevity\_penalty: 0.907
* ref\_len: 109538.0
* src\_name: English
* tgt\_name: Sino-Tibetan languages
* train\_date: 2020-08-01
* src\_alpha2: en
* tgt\_alpha2: sit
* prefer\_old: False
* long\_pair: eng-sit
* helsinki\_git\_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
* transformers\_git\_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
* port\_machine: brutasse
* port\_time: 2020-08-21-14:41
TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #en #sit #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### eng-sit


* source group: English
* target group: Sino-Tibetan languages
* OPUS readme: eng-sit
* model: transformer
* source language(s): eng
* target language(s): bod brx brx\_Latn cjy\_Hans cjy\_Hant cmn cmn\_Hans cmn\_Hant gan lzh lzh\_Hans mya nan wuu yue yue\_Hans yue\_Hant zho zho\_Hans zho\_Hant
* 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: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 23.5, chr-F: 0.217
testset: URL, BLEU: 23.2, chr-F: 0.223
testset: URL, BLEU: 25.0, chr-F: 0.230
testset: URL, BLEU: 20.2, chr-F: 0.225
testset: URL, BLEU: 0.4, chr-F: 0.147
testset: URL, BLEU: 0.5, chr-F: 0.012
testset: URL, BLEU: 25.7, chr-F: 0.223
testset: URL, BLEU: 0.2, chr-F: 0.222
testset: URL, BLEU: 29.2, chr-F: 0.249 ### System Info:


* hf\_name: eng-sit
* source\_languages: eng
* target\_languages: sit
* opus\_readme\_url: URL
* original\_repo: Tatoeba-Challenge
* tags: ['translation']
* languages: ['en', 'sit']
* src\_constituents: {'eng'}
* tgt\_constituents: set()
* src\_multilingual: False
* tgt\_multilingual: True
* prepro: normalization + SentencePiece (spm32k,spm32k)
* url\_model: URL
* url\_test\_set: URL
* src\_alpha3: eng
* tgt\_alpha3: sit
* short\_pair: en-sit
* chrF2\_score: 0.223
* bleu: 25.7
* brevity\_penalty: 0.907
* ref\_len: 109538.0
* src\_name: English
* tgt\_name: Sino-Tibetan languages
* train\_date: 2020-08-01
* src\_alpha2: en
* tgt\_alpha2: sit
* prefer\_old: False
* long\_pair: eng-sit
* helsinki\_git\_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
* transformers\_git\_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
* port\_machine: brutasse
* port\_time: 2020-08-21-14:41
passage: TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #en #sit #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
### eng-sit


* source group: English
* target group: Sino-Tibetan languages
* OPUS readme: eng-sit
* model: transformer
* source language(s): eng
* target language(s): bod brx brx\_Latn cjy\_Hans cjy\_Hant cmn cmn\_Hans cmn\_Hant gan lzh lzh\_Hans mya nan wuu yue yue\_Hans yue\_Hant zho zho\_Hans zho\_Hant
* 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: URL
* test set translations: URL
* test set scores: URL


Benchmarks
----------


testset: URL, BLEU: 23.5, chr-F: 0.217
testset: URL, BLEU: 23.2, chr-F: 0.223
testset: URL, BLEU: 25.0, chr-F: 0.230
testset: URL, BLEU: 20.2, chr-F: 0.225
testset: URL, BLEU: 0.4, chr-F: 0.147
testset: URL, BLEU: 0.5, chr-F: 0.012
testset: URL, BLEU: 25.7, chr-F: 0.223
testset: URL, BLEU: 0.2, chr-F: 0.222
testset: URL, BLEU: 29.2, chr-F: 0.249