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