| { |
| "packFormat": 1, |
| "direction": "fr-en", |
| "source": "fr", |
| "target": "en", |
| "model": { |
| "catalogueId": "translate-tc-big-fr-en", |
| "repo": "WindyTranslate/translate-tc-big-fr-en", |
| "revision": "4df75aab75047f16fef0821352fe3206392ea037", |
| "baseModel": "Helsinki-NLP/opus-mt-tc-big-fr-en" |
| }, |
| "licence": "CC-BY-4.0", |
| "attribution": "Based on OPUS-MT model Helsinki-NLP/opus-mt-tc-big-fr-en by Helsinki-NLP (Language Technology Research Group, University of Helsinki). Licensed CC-BY-4.0.", |
| "notice": "This product uses the model WindyTranslate/translate-tc-big-fr-en\n(https://huggingface.co/WindyTranslate/translate-tc-big-fr-en), published by Windstorm Labs (https://windstormlabs.com).\nBased on OPUS-MT model Helsinki-NLP/opus-mt-tc-big-fr-en by Helsinki-NLP (Language Technology Research Group, University of Helsinki). Licensed CC-BY-4.0.\nWindstorm Labs modified the upstream weights; the model card describes what was changed.\nLicensed under Creative Commons Attribution 4.0 International: https://creativecommons.org/licenses/by/4.0/", |
| "runtime": { |
| "engine": "onnxruntime", |
| "opset": 17, |
| "weights": "int8 (dynamic quantization, MatMul; embedding int8 shared)", |
| "files": { |
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| "decoder": "decoder.onnx", |
| "sharedEmbedding": "embed.bin (external data of both graphs; keep it next to them)", |
| "sourceTokenizer": "source.spm", |
| "targetTokenizer": "target.spm", |
| "vocab": "vocab.json", |
| "config": "model_config.json" |
| }, |
| "tokenizer": "SentencePiece PIECES from source.spm mapped to ids through vocab.json (unknown piece -> <unk>), then </s>. Raw SentencePiece ids are NOT model ids. Do not use onnxruntime-extensions' tokenizer op.", |
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| ], |
| "beam": 4, |
| "lengthNormalisation": "sum log-prob / output length", |
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| }, |
| "encoder": { |
| "inputs": [ |
| "input_ids [b,s] int64", |
| "attention_mask [b,s] int64" |
| ], |
| "outputs": [ |
| "cross_k_i / cross_v_i [b,16,s,64] for i in 0..5" |
| ] |
| }, |
| "decoder": { |
| "inputs": [ |
| "input_ids [b,1] int64 (start token on step 1, then the last token)", |
| "encoder_attention_mask [b,s] int64", |
| "past_k_i / past_v_i [b,16,t,64] float32 (t = 0 on step 1)", |
| "cross_k_i / cross_v_i (from the encoder)" |
| ], |
| "outputs": [ |
| "logits [b,1,vocab]", |
| "present_k_i / present_v_i [b,heads,t+1,head_dim] (next step's past)" |
| ] |
| } |
| }, |
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| "quality": { |
| "benchmark": "FLORES-200 devtest", |
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| "beam": 4, |
| "measured": "2026-10-17", |
| "by": "Windy Translate" |
| }, |
| "built": "2026-10-17T16:47:02Z", |
| "builder": "export_lean.py (Windy Translate)" |
| } |
