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Helsinki-NLP/opus-mt-fr-endecoder_model_merged.onnx 88 MBencoder_model.onnx 50 MBHelsinki-NLP/opus-mt-fr-en (revision c4aed37), exported to ONNX for on-device translation.
--task text2text-generation-with-past): one encoder and one merged decoder that handles both the first step and the cached steps (use_cache_branch input), so the decoder weights are stored once.quantize_dynamic, EnableSubgraph so the layers inside the merged decoder's branches are quantised too).| File | Purpose |
|---|---|
encoder_model.onnx |
Encoder |
decoder_model_merged.onnx |
Decoder with KV cache |
source.spm, target.spm |
SentencePiece models |
vocab.json |
Shared vocabulary |
config.json, generation_config.json |
Token IDs (eos, pad, decoder start) and generation settings |
With greedy decoding, the int8 files give the same output as the original PyTorch model on 24 of 30 short test phrases; the rest mostly differ in wording (quantisation).
The model is by the Language Technology Research Group at the University of Helsinki (OPUS-MT, Tiedemann & Thottingal, 2020), released under Apache-2.0; this conversion is released under the same licence.