- match: class: ktransformers.models.modeling_qwen3_next.Qwen3NextRotaryEmbedding replace: class: ktransformers.operators.RoPE.KQwen3MoeRotaryEmbedding kwargs: generate_device: "cuda" prefill_device: "cuda" - match: name: "^lm_head$" # regular expression class: torch.nn.Linear # only match modules matching name and class simultaneously replace: class: ktransformers.operators.linear.KTransformersLinear # optimized Kernel on quantized data types kwargs: generate_device: "cuda" prefill_device: "cuda" generate_op: "VLinearMarlin" prefill_op: "KLinearTorch" - match: name: "^model\\.layers\\.(?!.*mlp\\.shared_expert_gate).*$" # regular expression class: torch.nn.Linear # only match modules matching name and class simultaneously replace: class: ktransformers.operators.linear.KTransformersLinear # optimized Kernel on quantized data types kwargs: generate_device: "cuda" prefill_device: "cuda" generate_op: "KLinearMarlin" prefill_op: "KLinearTorch" - match: name: "^model\\.layers\\..*\\.mlp$" class: ktransformers.models.modeling_qwen3_next.Qwen3NextSparseMoeBlock replace: class: ktransformers.operators.experts.KQwen3NextSparseMoeBlockV2 # mlp module with custom forward function kwargs: generate_device: "cuda" prefill_device: "cuda" - match: name: "^model\\.layers\\..*\\.mlp\\.experts$" replace: class: ktransformers.operators.experts.KTransformersExpertsV2 # custom MoE Kernel with expert paralleism kwargs: prefill_device: "cuda" prefill_op: "KExpertsTorch" generate_device: "cpu" generate_op: "KExpertsCPU" out_device: "cuda" recursive: False # don't recursively inject submodules of this module - match: class: ktransformers.models.modeling_qwen3_next.Qwen3NextGatedDeltaNet replace: class: ktransformers.operators.balance_serve_attention.KQwen3NextGatedDeltaNet # optimized MLA implementation kwargs: generate_device: "cuda" prefill_device: "cuda" - match: class: ktransformers.models.modeling_qwen3_next.Qwen3NextAttention replace: class: ktransformers.operators.balance_serve_attention.KQwen3NextAttention # optimized MLA implementation kwargs: generate_device: "cuda" prefill_device: "cuda" - match: name: "^model.embed_tokens" replace: class: "default" kwargs: generate_device: "cpu" prefill_device: "cpu" - match: class: ktransformers.models.modeling_qwen3_next.Qwen3NextRMSNorm replace: class: ktransformers.operators.layernorm.KQwen3NextRMSNorm kwargs: generate_device: "cuda" prefill_device: "cuda" - match: class: ktransformers.models.modeling_qwen3_next.Qwen3NextMLP replace: class: ktransformers.operators.mlp.KQwen2MoeMLP kwargs: generate_device: "cuda" prefill_device: "cuda"