Downloads · 30 days
0
ben-xl8/wmt22-cometkiwi-da
wmt22-cometkiwi-da is a translation model from ben-xl8. Use it when you need text moved from one language to another. The card lists the license as cc-by-nc-sa-4.0.
This is a COMET quality estimation model by Unbabel: It receives a source sentence and the respective translation and returns a score that reflects the quality of the translation.
Downloads · 30 days
0
Access
Public
Updated Jul 11, 2023
Repo size
2.3 GB
Likes
1
Public
Click a slice to open those files.
.ckpt2.3 GB · 100%
From the Hugging Face model README
This is a COMET quality estimation model by Unbabel: It receives a source sentence and the respective translation and returns a score that reflects the quality of the translation.
CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task (Rei et al., WMT 2022)
cc-by-nc-sa-4.0
import json
import requests
API_URL = ""
API_TOKEN="MY_API_KEY"
headers = {
"Authorization": f"Bearer {API_TOKEN}",
"Content-Type": "application/json",
}
def query(url, headers, payload):
data = json.dumps(payload)
response = requests.request("POST", url, headers=headers, data=data)
return json.loads(response.content.decode("utf-8"))
payload = {
"inputs": {
"batch_size": 8,
"workers": None,
"data": [
{
"src": "Youll be picking fruit and generally helping us do all the usual farm work",
"mt": "당신은 과일을 따기도 하고 대체로 우리가 하는 일상적인 농장 일을 돕게 될 겁니다",
},{
"src": "Youll be picking fruit and generally helping us do all the usual farm work",
"mt": "당신은 과일을 따기도 하고 대체로 우리가 하는 일상적인 농장 일을 돕게 될 겁니다",
},{
"src": "Youll be picking fruit and generally helping us do all the usual farm work",
"mt": "당신은 과일을 따기도 하고 대체로 우리가 하는 일상적인 농장 일을 돕게 될 겁니다",
},{
"src": "Youll be picking fruit and generally helping us do all the usual farm work",
"mt": "당신은 과일을 따기도 하고 대체로 우리가 하는 일상적인 농장 일을 돕게 될 겁니다",
},{
"src": "Youll be picking fruit and generally helping us do all the usual farm work",
"mt": "당신은 과일을 따기도 하고 대체로 우리가 하는 일상적인 농장 일을 돕게 될 겁니다",
},{
"src": "Youll be picking fruit and generally helping us do all the usual farm work",
"mt": "당신은 과일을 따기도 하고 대체로 우리가 하는 일상적인 농장 일을 돕게 될 겁니다",
},{
"src": "Youll be picking fruit and generally helping us do all the usual farm work",
"mt": "당신은 과일을 따기도 하고 대체로 우리가 하는 일상적인 농장 일을 돕게 될 겁니다",
},
]
}
}
scores = query(API_URL, headers, payload)
Unbabel's model is intented to be used for reference-free MT evaluation.
Given a source text and its translation, outputs a single score between 0 and 1 where 1 represents a perfect translation.
This model builds on top of InfoXLM which cover the following languages:
Afrikaans, Albanian, Amharic, Arabic, Armenian, Assamese, Azerbaijani, Basque, Belarusian, Bengali, Bengali Romanized, Bosnian, Breton, Bulgarian, Burmese, Burmese, Catalan, Chinese (Simplified), Chinese (Traditional), Croatian, Czech, Danish, Dutch, English, Esperanto, Estonian, Filipino, Finnish, French, Galician, Georgian, German, Greek, Gujarati, Hausa, Hebrew, Hindi, Hindi Romanized, Hungarian, Icelandic, Indonesian, Irish, Italian, Japanese, Javanese, Kannada, Kazakh, Khmer, Korean, Kurdish (Kurmanji), Kyrgyz, Lao, Latin, Latvian, Lithuanian, Macedonian, Malagasy, Malay, Malayalam, Marathi, Mongolian, Nepali, Norwegian, Oriya, Oromo, Pashto, Persian, Polish, Portuguese, Punjabi, Romanian, Russian, Sanskri, Scottish, Gaelic, Serbian, Sindhi, Sinhala, Slovak, Slovenian, Somali, Spanish, Sundanese, Swahili, Swedish, Tamil, Tamil Romanized, Telugu, Telugu Romanized, Thai, Turkish, Ukrainian, Urdu, Urdu Romanized, Uyghur, Uzbek, Vietnamese, Welsh, Western, Frisian, Xhosa, Yiddish.
Thus, results for language pairs containing uncovered languages are unreliable!