fairseq
https://github.com/facebookresearch/fairseq
Python
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
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- Issues
- Actor-Critic NMT
- device_id is not set properly when _infer_torch_distributed_launch_init is called
- matmul+as_strided consumes more memory than skew+matmul
- Expected 3-dimensional input for 3-dimensional weight
- The exact English pretraining data and Chinese pretraining data that are exact same to the BERT paper's pretraining data.
- Validation set and development set clarification for fine-tuning RoBERTa with Quant-Noise.
- Multilingual Translation
- Finetuning m2m Multilingual Model
- Argument "need_head_weights" ignored/not triggered in some cases in MultiheadAttention class
- How can I iteretively conduct inference and training?
- Docs
- Python not yet supported