This is a Deutsch-English machine translation model based on non-autoregressive Transformer topology.
Tokenization occurs using the SentencePieceBPETokenizer (see the demo code for implementation details) and the enclosed tokenizer_src and tokenizer_tgt folders.
Metric | Value |
---|---|
GOps | 23.19 |
MParams | 77.47 |
Source framework | PyTorch* |
The quality metrics were calculated on the wmt19-en-de dataset (test
split in lower case).
Metric | Value |
---|---|
BLEU | 21.4 % |
Use accuracy_check [...] --model_attributes <path_to_folder_with_downloaded_model>
to specify the path to additional model attributes. path_to_folder_with_downloaded_model
is a path to the folder, where the current model is downloaded by Model Downloader tool.
name: tokens
shape: 1, 150
description: sequence of tokens (integer values) representing the tokenized sentence.
The sequence structure is as follows (<s>
, </s>
and <pad>
should be replaced by corresponding token IDs as specified by the dictionary):
<s>
+ tokenized sentence + </s>
+ (<pad>
tokens to pad to the maximum sequence length of 150)
name: pred
shape: 1, 200
description: sequence of tokens (integer values) representing the tokenized translation.
The sequence structure is as follows (<s>
, </s>
and <pad>
should be replaced by corresponding token IDs as specified by the dictionary):
<s>
+ tokenized sentence + </s>
+ (<pad>
tokens to pad to the maximum sequence length of 150)
The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:
[*] Other names and brands may be claimed as the property of others.