fairseq
https://github.com/facebookresearch/fairseq
Python
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
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- Issues
- fix collater exception with TransformEosLangPairDataset
- Really slow training in pretraining phase using wav2vec2 while memory is consumed
- Config for Wav2Vec2 training from scratch
- Validation Accuracy - Finetuning ROBERTA on Glue Tasks
- Fix tlayer torch JIT export
- when I train with transformer_align model，Error happened training one of my training set, other datasets are ok。
- The quantized model inference speed is slower than the non-quantized model.
- best_checkpoint_metric as f1
- HELP
- NLLB vocabulary missing common Chinese character/tokens
- Docs
- Python not yet supported