OpenNMT-py v3.2.0
Lots new stuff in this release:
- Skip init during model build (way faster building)
- Enable quantization of LoRA layers
- Enable 4bit quantization from bitsandbytes (NF4 / FP4)
- Enable "some" bnb.optim Optimizers for benchmarking purpose
- Refactor model state_dict loading to enable pseudo lazy loading with move on GPU as it loads
- Enable Gradient checkpointing for FFN, MHA, LoRA modules
- Make FFN bias optional (same as QKV): llama, mpt, redpajama, openllama converters changed accordingly.
Convertv2_v3 set add_qkvbias=True, add_ffnbias=True.
load_checkpoint: if w1_bias detected in checkpoint then add_ffnbias=True - Add Multi Query attention
- Add Parallel Residual attention
- Add Falcon 7B converter