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Create recipe.yaml

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  1. recipe.yaml +37 -0
recipe.yaml ADDED
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+ test_stage:
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+ obcq_modifiers:
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+ SmoothQuantModifier:
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+ smoothing_strength: 0.5
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+ mappings: [
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+ [["re:.*q_proj", "re:.*k_proj", "re:.*v_proj"], "re:.*input_layernorm"],
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+ [["re:.*gate_proj", "re:.*up_proj"], "re:.*post_attention_layernorm"]
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+ ]
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+ QuantizationModifier:
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+ ignore:
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+ # These operations don't make sense to quantize
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+ - LlamaRotaryEmbedding
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+ - LlamaRMSNorm
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+ - SiLUActivation
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+ # Skip quantizing the BMMs
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+ - QuantizableMatMul
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+ # Skip quantizing the layers with the most sensitive activations
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+ - model.layers.1.mlp.down_proj
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+ - model.layers.46.mlp.down_proj
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+ - model.layers.47.mlp.down_proj
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+ - model.layers.46.mlp.gate_proj
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+ - model.layers.46.mlp.up_proj
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+ post_oneshot_calibration: true
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+ scheme_overrides:
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+ Embedding:
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+ input_activations: null
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+ weights:
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+ num_bits: 8
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+ symmetric: false
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+ SparseGPTModifier:
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+ sparsity: 0.5
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+ block_size: 128
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+ sequential_update: true
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+ quantize: true
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+ percdamp: 0.01
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+ mask_structure: "0:0"
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+ targets: ["re:model.layers.\\d*$"]