fairseq
https://github.com/facebookresearch/fairseq
Python
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
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- Issues
- Beam search "cands_to_ignore" is not used correctly.
- Too low BLEU score in reproducing simultaneous speech translation (MuST-C en-de)
- Bidirectional translation with different datasets
- ADAM KeyError: 'max_exp_avg_sq' when further pretraining XLSR 53 on Portuguese Data
- For `FileAudioDataset`, allow manifests to specify short segments of longer audio files
- calculating cer along with wer in infer.py
- Textless NLP: missing tacotron2 training script for GSLM
- Textless NLP metrics : absence of script dummy_asr_data.py
- Broken links for (transformer-based) translation models with torch.hub.load
- 'hubert_pretraining' not in tasks.TASK_REGISTRY
- Docs
- Python not yet supported