Nemotron74ba9
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It's done in context of porting `HIL-SERL` paper code (https://hil-serl.github.io/) to `Lerobot` (https://github.com/Lerobot/lerobot). The HF doesn't have ResNet-10 model, which could be pretty usefult for robotics tasks because of it's small size. This model is converted from JAX to PyTorch, and the weights are preserved. This model is a PyTorch port of the original JAX implementation. The conversion maintains the original model's architecture and weights while making it accessible to PyTorch users. The original model is from https://github.com/rail-berkeley/hil-serl/blob/7d17d13560d85abffbd45facec17c4f9189c29c0/serl_launcher/serl_launcher/utils/train_utils.py#L103. This model was converted using an automated JAX to PyTorch conversion pipeline, ensuring: - Weight preservation - Architecture matching - Numerical stability
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* source languages: ar * target languages: en * OPUS readme: ar-en * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: opus-2019-12-18.zip * test set translations: opus-2019-12-18.test.txt * test set scores: opus-2019-12-18.eval.txt
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* source languages: da * target languages: en * OPUS readme: da-en * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: opus-2019-12-18.zip * test set translations: opus-2019-12-18.test.txt * test set scores: opus-2019-12-18.eval.txt
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* source languages: de * target languages: en * OPUS readme: de-en * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: opus-2020-02-26.zip * test set translations: opus-2020-02-26.test.txt * test set scores: opus-2020-02-26.eval.txt
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