[pull] main from inclusionAI:main#19
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pull[bot] merged 1 commit intoaxistore80-coder:mainfrom Mar 27, 2026
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… + CP (#1079) * feat: add BailingMoeV2.5 support with Lightning Attention + MLA + MoE + CP Add support for BailingMoeV2.5 model architecture featuring: - Lightning Attention with causal linear attention mechanism - Multi-Latent Attention (MLA) with KV compression - Mixture of Experts (MoE) with 256 experts and top-8 routing - Context Parallelism (CP) support for long sequences - HuggingFace checkpoint loading and Megatron bridge - Recovery optimizer skip for distributed optimizer compatibility * fix(hf_save): use clamped _max_workers for expert shard ThreadPoolExecutor The expert shard save path was passing the raw `max_workers` parameter (possibly None) instead of the computed `_max_workers`, causing Python to default to min(32, cpu_count+4) threads. This aligns the expert path with the non-expert path which already uses `_max_workers`. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: sync BailingHybrid/MLA fixes from adapt-ling25-model Cherry-pick non-SWE Bailing-related changes from chucai.dzq/adapt-ling25-model: From 32a7d39: - Register bailing_moe_v2 in BailingMoeBridge - Fix TP all-gather for MLA duplicated params (linear_q_down_proj, linear_kv_down_proj) by passing duplicated_param_names set instead of dead parallel_mode check - Add _weight_merge_across_tp override for MLA duplicated weights during save - Add _patch_saved_config to restore model_type and torch_dtype in saved config.json - Copy chat_template files during HF config copy From 58304de: - Minor formatting fixes in RecoverConfig and recover.py Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: chucai.dzq <chucai.dzq@alibaba-inc.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
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