Update README.md
Browse files
README.md
CHANGED
@@ -32,7 +32,7 @@ language:
|
|
32 |
license: apache-2.0
|
33 |
---
|
34 |
|
35 |
-
This is a [AfriCOMET-QE-STL (single task)](https://github.com/masakhane-io/africomet) evaluation model: It receives a
|
36 |
|
37 |
# Paper
|
38 |
|
@@ -54,7 +54,7 @@ pip install unbabel-comet
|
|
54 |
Then you can use it through comet CLI:
|
55 |
|
56 |
```bash
|
57 |
-
comet-score -s {source-inputs}.txt -t {translation-outputs}.txt
|
58 |
```
|
59 |
|
60 |
Or using Python:
|
@@ -68,12 +68,10 @@ data = [
|
|
68 |
{
|
69 |
"src": "Nadal sàkọọ́lẹ̀ ìforígbárí o ní àmì méje sóódo pẹ̀lú ilẹ̀ Canada.",
|
70 |
"mt": "Nadal's head to head record against the Canadian is 7–2.",
|
71 |
-
"ref": "Nadal scored seven unanswered points against Canada."
|
72 |
},
|
73 |
{
|
74 |
"src": "Laipe yi o padanu si Raoniki ni ere Sisi Brisbeni.",
|
75 |
"mt": "He recently lost against Raonic in the Brisbane Open.",
|
76 |
-
"ref": "He recently lost to Raoniki in the game Sisi Brisbeni."
|
77 |
}
|
78 |
]
|
79 |
model_output = model.predict(data, batch_size=8, gpus=1)
|
@@ -82,9 +80,9 @@ print (model_output)
|
|
82 |
|
83 |
# Intended uses
|
84 |
|
85 |
-
Our model is intented to be used for **MT
|
86 |
|
87 |
-
Given a
|
88 |
|
89 |
# Languages Covered:
|
90 |
|
|
|
32 |
license: apache-2.0
|
33 |
---
|
34 |
|
35 |
+
This is a [AfriCOMET-QE-STL (quality estimation single task)](https://github.com/masakhane-io/africomet) evaluation model: It receives a source sentence, and a translation, and returns a score that reflects the quality of the translation compared to the source.
|
36 |
|
37 |
# Paper
|
38 |
|
|
|
54 |
Then you can use it through comet CLI:
|
55 |
|
56 |
```bash
|
57 |
+
comet-score -s {source-inputs}.txt -t {translation-outputs}.txt --model masakhane/africomet-qe-stl
|
58 |
```
|
59 |
|
60 |
Or using Python:
|
|
|
68 |
{
|
69 |
"src": "Nadal sàkọọ́lẹ̀ ìforígbárí o ní àmì méje sóódo pẹ̀lú ilẹ̀ Canada.",
|
70 |
"mt": "Nadal's head to head record against the Canadian is 7–2.",
|
|
|
71 |
},
|
72 |
{
|
73 |
"src": "Laipe yi o padanu si Raoniki ni ere Sisi Brisbeni.",
|
74 |
"mt": "He recently lost against Raonic in the Brisbane Open.",
|
|
|
75 |
}
|
76 |
]
|
77 |
model_output = model.predict(data, batch_size=8, gpus=1)
|
|
|
80 |
|
81 |
# Intended uses
|
82 |
|
83 |
+
Our model is intented to be used for **MT quality estimation**.
|
84 |
|
85 |
+
Given a source sentence and a translation outputs a single score between 0 and 1 where 1 represents a perfect translation.
|
86 |
|
87 |
# Languages Covered:
|
88 |
|