Add multilingual to the language tag
#2
by
lbourdois
- opened
README.md
CHANGED
@@ -2,97 +2,91 @@
|
|
2 |
language:
|
3 |
- en
|
4 |
- fi
|
|
|
|
|
5 |
tags:
|
6 |
- translation
|
7 |
- opus-mt-tc
|
8 |
-
license: cc-by-4.0
|
9 |
model-index:
|
10 |
- name: opus-mt-tc-big-en-fi
|
11 |
results:
|
12 |
- task:
|
13 |
-
name: Translation eng-fin
|
14 |
type: translation
|
15 |
-
|
16 |
dataset:
|
17 |
name: flores101-devtest
|
18 |
type: flores_101
|
19 |
args: eng fin devtest
|
20 |
metrics:
|
21 |
-
-
|
22 |
-
type: bleu
|
23 |
value: 27.6
|
|
|
24 |
- task:
|
25 |
-
name: Translation eng-fin
|
26 |
type: translation
|
27 |
-
|
28 |
dataset:
|
29 |
name: newsdev2015
|
30 |
type: newsdev2015
|
31 |
args: eng-fin
|
32 |
metrics:
|
33 |
-
-
|
34 |
-
type: bleu
|
35 |
value: 24.2
|
|
|
36 |
- task:
|
37 |
-
name: Translation eng-fin
|
38 |
type: translation
|
39 |
-
|
40 |
dataset:
|
41 |
name: tatoeba-test-v2021-08-07
|
42 |
type: tatoeba_mt
|
43 |
args: eng-fin
|
44 |
metrics:
|
45 |
-
-
|
46 |
-
type: bleu
|
47 |
value: 39.3
|
|
|
48 |
- task:
|
49 |
-
name: Translation eng-fin
|
50 |
type: translation
|
51 |
-
|
52 |
dataset:
|
53 |
name: newstest2015
|
54 |
type: wmt-2015-news
|
55 |
args: eng-fin
|
56 |
metrics:
|
57 |
-
-
|
58 |
-
type: bleu
|
59 |
value: 26.4
|
|
|
60 |
- task:
|
61 |
-
name: Translation eng-fin
|
62 |
type: translation
|
63 |
-
|
64 |
dataset:
|
65 |
name: newstest2016
|
66 |
type: wmt-2016-news
|
67 |
args: eng-fin
|
68 |
metrics:
|
69 |
-
-
|
70 |
-
type: bleu
|
71 |
value: 28.8
|
|
|
72 |
- task:
|
73 |
-
name: Translation eng-fin
|
74 |
type: translation
|
75 |
-
|
76 |
dataset:
|
77 |
name: newstest2017
|
78 |
type: wmt-2017-news
|
79 |
args: eng-fin
|
80 |
metrics:
|
81 |
-
-
|
82 |
-
type: bleu
|
83 |
value: 31.3
|
|
|
84 |
- task:
|
85 |
-
name: Translation eng-fin
|
86 |
type: translation
|
87 |
-
|
88 |
dataset:
|
89 |
name: newstest2019
|
90 |
type: wmt-2019-news
|
91 |
args: eng-fin
|
92 |
metrics:
|
93 |
-
-
|
94 |
-
type: bleu
|
95 |
value: 26.4
|
|
|
96 |
---
|
97 |
# opus-mt-tc-big-en-fi
|
98 |
|
@@ -100,7 +94,7 @@ Neural machine translation model for translating from English (en) to Finnish (f
|
|
100 |
|
101 |
This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train).
|
102 |
|
103 |
-
* Publications: [OPUS-MT
|
104 |
|
105 |
```
|
106 |
@inproceedings{tiedemann-thottingal-2020-opus,
|
@@ -164,7 +158,7 @@ for t in translated:
|
|
164 |
print( tokenizer.decode(t, skip_special_tokens=True) )
|
165 |
|
166 |
# expected output:
|
167 |
-
#
|
168 |
# Kosketa puuta!
|
169 |
```
|
170 |
|
@@ -175,7 +169,7 @@ from transformers import pipeline
|
|
175 |
pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-fi")
|
176 |
print(pipe("Russia is big."))
|
177 |
|
178 |
-
# expected output:
|
179 |
```
|
180 |
|
181 |
## Benchmarks
|
@@ -200,7 +194,7 @@ print(pipe("Russia is big."))
|
|
200 |
|
201 |
## Acknowledgements
|
202 |
|
203 |
-
The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union
|
204 |
|
205 |
## Model conversion info
|
206 |
|
|
|
2 |
language:
|
3 |
- en
|
4 |
- fi
|
5 |
+
- multilingual
|
6 |
+
license: cc-by-4.0
|
7 |
tags:
|
8 |
- translation
|
9 |
- opus-mt-tc
|
|
|
10 |
model-index:
|
11 |
- name: opus-mt-tc-big-en-fi
|
12 |
results:
|
13 |
- task:
|
|
|
14 |
type: translation
|
15 |
+
name: Translation eng-fin
|
16 |
dataset:
|
17 |
name: flores101-devtest
|
18 |
type: flores_101
|
19 |
args: eng fin devtest
|
20 |
metrics:
|
21 |
+
- type: bleu
|
|
|
22 |
value: 27.6
|
23 |
+
name: BLEU
|
24 |
- task:
|
|
|
25 |
type: translation
|
26 |
+
name: Translation eng-fin
|
27 |
dataset:
|
28 |
name: newsdev2015
|
29 |
type: newsdev2015
|
30 |
args: eng-fin
|
31 |
metrics:
|
32 |
+
- type: bleu
|
|
|
33 |
value: 24.2
|
34 |
+
name: BLEU
|
35 |
- task:
|
|
|
36 |
type: translation
|
37 |
+
name: Translation eng-fin
|
38 |
dataset:
|
39 |
name: tatoeba-test-v2021-08-07
|
40 |
type: tatoeba_mt
|
41 |
args: eng-fin
|
42 |
metrics:
|
43 |
+
- type: bleu
|
|
|
44 |
value: 39.3
|
45 |
+
name: BLEU
|
46 |
- task:
|
|
|
47 |
type: translation
|
48 |
+
name: Translation eng-fin
|
49 |
dataset:
|
50 |
name: newstest2015
|
51 |
type: wmt-2015-news
|
52 |
args: eng-fin
|
53 |
metrics:
|
54 |
+
- type: bleu
|
|
|
55 |
value: 26.4
|
56 |
+
name: BLEU
|
57 |
- task:
|
|
|
58 |
type: translation
|
59 |
+
name: Translation eng-fin
|
60 |
dataset:
|
61 |
name: newstest2016
|
62 |
type: wmt-2016-news
|
63 |
args: eng-fin
|
64 |
metrics:
|
65 |
+
- type: bleu
|
|
|
66 |
value: 28.8
|
67 |
+
name: BLEU
|
68 |
- task:
|
|
|
69 |
type: translation
|
70 |
+
name: Translation eng-fin
|
71 |
dataset:
|
72 |
name: newstest2017
|
73 |
type: wmt-2017-news
|
74 |
args: eng-fin
|
75 |
metrics:
|
76 |
+
- type: bleu
|
|
|
77 |
value: 31.3
|
78 |
+
name: BLEU
|
79 |
- task:
|
|
|
80 |
type: translation
|
81 |
+
name: Translation eng-fin
|
82 |
dataset:
|
83 |
name: newstest2019
|
84 |
type: wmt-2019-news
|
85 |
args: eng-fin
|
86 |
metrics:
|
87 |
+
- type: bleu
|
|
|
88 |
value: 26.4
|
89 |
+
name: BLEU
|
90 |
---
|
91 |
# opus-mt-tc-big-en-fi
|
92 |
|
|
|
94 |
|
95 |
This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train).
|
96 |
|
97 |
+
* Publications: [OPUS-MT � Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge � Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.)
|
98 |
|
99 |
```
|
100 |
@inproceedings{tiedemann-thottingal-2020-opus,
|
|
|
158 |
print( tokenizer.decode(t, skip_special_tokens=True) )
|
159 |
|
160 |
# expected output:
|
161 |
+
# Ven�j� on suuri.
|
162 |
# Kosketa puuta!
|
163 |
```
|
164 |
|
|
|
169 |
pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-fi")
|
170 |
print(pipe("Russia is big."))
|
171 |
|
172 |
+
# expected output: Ven�j� on suuri.
|
173 |
```
|
174 |
|
175 |
## Benchmarks
|
|
|
194 |
|
195 |
## Acknowledgements
|
196 |
|
197 |
+
The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union�s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union�s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland.
|
198 |
|
199 |
## Model conversion info
|
200 |
|