zho-eng
Table of Contents
- Model Details
- Uses
- Risks, Limitations and Biases
- Training
- Evaluation
- Citation Information
- How to Get Started With the Model
Model Details
- Model Description:
- Developed by: Algmon
- Model Type: Translation
- Language(s):
- Source Language: Chinese
- Target Language: English
- License: CC-BY-4.0
- Resources for more information:
Uses
Direct Use
This model can be used for translation and text-to-text generation.
Risks, Limitations, and Biases
CONTENT WARNING: Readers should be aware this section contains content that is disturbing, offensive, and can propagate historical and current stereotypes.
Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)).
Further details about the dataset for this model can be found in the OPUS readme: zho-eng
Training
System Information
- helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
- transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
- port_machine: brutasse
- port_time: 2020-08-21-14:41
- src_multilingual: False
- tgt_multilingual: False
Training Data
Preprocessing
-
pre-processing: normalization + SentencePiece (spm32k,spm32k)
-
ref_len: 82826.0
-
dataset: opus
-
download original weights: opus-2020-07-17.zip
-
test set translations: opus-2020-07-17.test.txt
Evaluation
Results
-
test set scores: opus-2020-07-17.eval.txt
-
brevity_penalty: 0.948
Benchmarks
testset | BLEU | chr-F |
---|---|---|
Tatoeba-test.zho.eng | 36.1 | 0.548 |
How to Get Started With the Model
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-zh-en")
model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-zh-en")