New features
- 🔥Support contamination-free packing via the
neat_packing
argument by @chuan298 in #4224 - 🔥Support split evaluation via the
eval_dataset
argument by @codemayq in #4691 - 🔥Support HQQ/EETQ quantization via the
quantization_method
argument by @hiyouga - 🔥Support ZeRO-3 when using BAdam by @Ledzy in #4352
- Support train on the last turn via the
mask_history
argument by @aofengdaxia in #4878 - Add NPU Dockerfile by @MengqingCao in #4355
- Support building FlashAttention2 in Dockerfile by @hzhaoy in #4461
- Support
batch_eval_metrics
at evaluation by @hiyouga
New models
- Base models
- InternLM2.5-7B 📄
- Gemma2 (9B/27B) 📄
- Instruct/Chat models
Changes
- Fix DPO cutoff len and deprecate
reserved_label_len
argument - Improve loss function for reward modeling
Bug fix
- Fix numpy version by @MengqingCao in #4382
- Improve cli by @kno10 in #4409
- Add
tool_format
parameter to control prompt by @mMrBun in #4417 - Automatically label npu issue by @MengqingCao in #4445
- Fix flash_attn args by @stceum in #4446
- Fix docker-compose path by @MengqingCao in #4544
- Fix torch-npu dependency by @hashstone in #4561
- Fix deepspeed + pissa by @hzhaoy in #4580
- Improve cli by @injet-zhou in #4590
- Add project by @wzh1994 in #4662
- Fix docstring by @hzhaoy in #4673
- Fix Windows command preview in WebUI by @marko1616 in #4700
- Fix vllm 0.5.1 by @T-Atlas in #4706
- Fix save value head model callback by @yzoaim in #4746
- Fix CUDA Dockerfile by @hzhaoy in #4781
- Fix examples by @codemayq in #4804
- Fix evaluation data split by @codemayq in #4821
- Fix CI by @codemayq in #4822
- Fix #2290 #3974 #4113 #4379 #4398 #4402 #4410 #4419 #4432 #4456 #4458 #4549 #4556 #4579 #4592 #4609 #4617 #4674 #4677 #4683 #4684 #4699 #4705 #4731 #4742 #4779 #4780 #4786 #4792 #4820 #4826