File size: 1,464 Bytes
b836d92
 
 
 
 
 
 
 
156352a
b836d92
 
 
765a274
 
b836d92
 
 
 
4e6b43b
 
b836d92
 
 
 
4e6b43b
 
 
b836d92
 
 
 
 
 
e5ad988
 
 
 
 
b836d92
 
 
 
 
 
 
 
e5ad988
b836d92
e5ad988
 
 
 
b836d92
 
 
e5ad988
b836d92
 
 
 
 
 
 
4e6b43b
 
 
 
b836d92
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
---
language: 
- ca
- en

tags:
- translation

library_name: opennmt
license: mit
metrics:
- bleu

inference: false
---

### Introduction

English - Catalan translation model based on OpenNMT. These are the same models that we have in production at https://www.softcatala.org/traductor/.


### Usage


```bash
pip3 install ctranslate2 pyonmttok
```

Simple translation using Python:

```python

import ctranslate2
from huggingface_hub import snapshot_download
model_dir = snapshot_download(repo_id="softcatala/opennmt-eng-cat", revision="main")

translator = ctranslate2.Translator(model_dir)
print(translator.translate_batch([["▁Hello", "▁world", "!"]]))
[[{'tokens': ['▁Hola', '▁món', '!']}]]

```

Simple tokenization & translation using Python:


```python
import ctranslate2
import pyonmttok
from huggingface_hub import snapshot_download
model_dir = snapshot_download(repo_id="softcatala/opennmt-eng-cat", revision="main")

tokenizer=pyonmttok.Tokenizer(mode="none", sp_model_path = model_dir + "/sp_m.model")
tokenized=tokenizer.tokenize("Hello world!")

import ctranslate2
translator = ctranslate2.Translator(model_dir)
translated = translator.translate_batch([tokenized[0]])
print(tokenizer.detokenize(translated[0][0]['tokens']))
Hola món!
```

## Benchmarks

| testset                               | BLEU  |
|---------------------------------------|-------|
| test dataset (from train/dev/test)   	| 45.2	|
| Flores101 dataset  					| 40.7	|