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weijiang2009/AlgmonMTModel
AlgmonMTModel is a translation model from weijiang2009. Use it when you need text moved from one language to another. It is set up for transformers. The card lists the license as cc-by-4.0.
- Model Details - Uses - Risks, Limitations and Biases - Training - Evaluation - Citation Information - How to Get Started With the Model
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From the Hugging Face model README
This model can be used for translation and text-to-text generation.
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
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
test set scores: opus-2020-07-17.eval.txt
brevity_penalty: 0.948
| testset | BLEU | chr-F |
|---|---|---|
| Tatoeba-test.zho.eng | 36.1 | 0.548 |
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")