model: name: Kimi-K2-Thinking model_type: kimik2 paths: checkpoint_dir: /home/models/kimi/Kimi-K2.5 output_dir: /home/models/kimi/Kimi-K2.5-w4a8 runtime: num_workers: 16 mode: dequant+quant # dequant | dequant+quant | quant (only support bf16) retry_files: ~ quant: version: 2 format: TN: - "re:model.layers.\\d+.mlp.experts.*" - "re:.*shared_experts.*" - "re:model.layers.\\d+.self_attn.q_a_proj.*" - "re:model.layers.\\d+.self_attn.q_b_proj.*" - "re:model.layers.\\d+.self_attn.kv_a_proj_with_mqa.*" - "re:model.layers.\\d+.self_attn.kv_b_proj.*" - "re:model.layers.\\d+.self_attn.o_proj.*" - "re:model.layers.\\d+.mlp.shared_experts.*" - "re:model.layers.\\d+.mlp.gate_proj.*" - "re:model.layers.\\d+.mlp.down_proj.*" - "re:model.layers.\\d+.mlp.up_proj.*" NN: ~ batch_size: 64 block_size: 128 group_size: -1 symmetric: True class: int4: - "re:model.layers.\\d+.mlp.experts.*" int8: - "re:.*shared_experts.*" - "re:model.layers.\\d+.self_attn.q_a_proj.*" - "re:model.layers.\\d+.self_attn.q_b_proj.*" - "re:model.layers.\\d+.self_attn.kv_a_proj_with_mqa.*" - "re:model.layers.\\d+.self_attn.kv_b_proj.*" - "re:model.layers.\\d+.self_attn.o_proj.*" - "re:model.layers.\\d+.mlp.shared_experts.*" - "re:model.layers.\\d+.mlp.gate_proj.*" - "re:model.layers.\\d+.mlp.down_proj.*" - "re:model.layers.\\d+.mlp.up_proj.*" ignore: - "re:model.layers.\\d+.self_attn.q_a_layernorm.*" - "re:model.layers.\\d+.self_attn.kv_a_layernorm.*" - "re:model.layers.\\d+.input_layernorm.*" - "re:model.layers.\\d+.post_attention_layernorm.*" - "re:model.layers.\\d+.mlp.gate.weight" - "re:model.layers.\\d+.mlp.gate.e_score_correction_bias" - "re:model.layers.\\d+.self_attn.rotary_emb.inv_freq" - "re:model.embed_tokens.*" - "re:model.norm.*" - "re:lm_head.*" dequant: ignore: - "re:lm_head.*" - "re:.*self_attn.*" - "re:.*shared_experts.*" - "re:.*mlp\\.(gate|up|gate_up|down)_proj.*" - "re:model.layers.\\d+.mlp.gate.e_score_correction_bias" - "re:model.layers.\\d+.input_layernorm.weight" - "re:model.layers.\\d+.post_attention_layernorm.weight" - "re:model.layers.\\d+.mlp.gate.weight" - "re:model.layers.\\d+.self_attn.rotary_emb.inv_freq" - "re:model.norm.*" - "re:model.layers.\\d+.self_attn.q_a_layernorm.*" - "re:model.layers.\\d+.self_attn.kv_a_layernorm.*" - "re:model.embed_tokens.*"