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gguf-dump : support i-quants (#5841)

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Co-authored-by: Black_Fox <radekliska@gmail.com>
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Nindaleth 2024-03-03 09:43:42 +01:00 committed by GitHub
parent de9692a7d2
commit 87c2e8b279
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1 changed files with 44 additions and 28 deletions
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gguf-py/gguf/constants.py
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@ -604,20 +604,28 @@ class PoolingType(IntEnum):
class GGMLQuantizationType(IntEnum): class GGMLQuantizationType(IntEnum):
F32 = 0 F32 = 0
F16 = 1 F16 = 1
Q4_0 = 2 Q4_0 = 2
Q4_1 = 3 Q4_1 = 3
Q5_0 = 6 Q5_0 = 6
Q5_1 = 7 Q5_1 = 7
Q8_0 = 8 Q8_0 = 8
Q8_1 = 9 Q8_1 = 9
Q2_K = 10 Q2_K = 10
Q3_K = 11 Q3_K = 11
Q4_K = 12 Q4_K = 12
Q5_K = 13 Q5_K = 13
Q6_K = 14 Q6_K = 14
Q8_K = 15 Q8_K = 15
IQ2_XXS = 16
IQ2_XS = 17
IQ3_XXS = 18
IQ1_S = 19
IQ4_NL = 20
IQ3_S = 21
IQ2_S = 22
IQ4_XS = 23
class GGUFEndian(IntEnum): class GGUFEndian(IntEnum):
@ -662,20 +670,28 @@ class GGUFValueType(IntEnum):
QK_K = 256 QK_K = 256
# Items here are (block size, type size) # Items here are (block size, type size)
GGML_QUANT_SIZES = { GGML_QUANT_SIZES = {
GGMLQuantizationType.F32: (1, 4), GGMLQuantizationType.F32: (1, 4),
GGMLQuantizationType.F16: (1, 2), GGMLQuantizationType.F16: (1, 2),
GGMLQuantizationType.Q4_0: (32, 2 + 16), GGMLQuantizationType.Q4_0: (32, 2 + 16),
GGMLQuantizationType.Q4_1: (32, 2 + 2 + 16), GGMLQuantizationType.Q4_1: (32, 2 + 2 + 16),
GGMLQuantizationType.Q5_0: (32, 2 + 4 + 16), GGMLQuantizationType.Q5_0: (32, 2 + 4 + 16),
GGMLQuantizationType.Q5_1: (32, 2 + 2 + 4 + 16), GGMLQuantizationType.Q5_1: (32, 2 + 2 + 4 + 16),
GGMLQuantizationType.Q8_0: (32, 2 + 32), GGMLQuantizationType.Q8_0: (32, 2 + 32),
GGMLQuantizationType.Q8_1: (32, 4 + 4 + 32), GGMLQuantizationType.Q8_1: (32, 4 + 4 + 32),
GGMLQuantizationType.Q2_K: (256, 2 + 2 + QK_K // 16 + QK_K // 4), GGMLQuantizationType.Q2_K: (256, 2 + 2 + QK_K // 16 + QK_K // 4),
GGMLQuantizationType.Q3_K: (256, 2 + QK_K // 4 + QK_K // 8 + 12), GGMLQuantizationType.Q3_K: (256, 2 + QK_K // 4 + QK_K // 8 + 12),
GGMLQuantizationType.Q4_K: (256, 2 + 2 + QK_K // 2 + 12), GGMLQuantizationType.Q4_K: (256, 2 + 2 + QK_K // 2 + 12),
GGMLQuantizationType.Q5_K: (256, 2 + 2 + QK_K // 2 + QK_K // 8 + 12), GGMLQuantizationType.Q5_K: (256, 2 + 2 + QK_K // 2 + QK_K // 8 + 12),
GGMLQuantizationType.Q6_K: (256, 2 + QK_K // 2 + QK_K // 4 + QK_K // 16), GGMLQuantizationType.Q6_K: (256, 2 + QK_K // 2 + QK_K // 4 + QK_K // 16),
GGMLQuantizationType.Q8_K: (256, 4 + QK_K + QK_K // 8), GGMLQuantizationType.Q8_K: (256, 4 + QK_K + QK_K // 8),
GGMLQuantizationType.IQ2_XXS: (256, 2 + QK_K // 4),
GGMLQuantizationType.IQ2_XS: (256, 2 + QK_K // 4 + QK_K // 32),
GGMLQuantizationType.IQ3_XXS: (256, 2 + QK_K // 4 + QK_K // 8),
GGMLQuantizationType.IQ1_S: (256, 2 + QK_K // 8 + QK_K // 16),
GGMLQuantizationType.IQ4_NL: (32, 2 + 16),
GGMLQuantizationType.IQ3_S: (256, 2 + QK_K // 4 + QK_K // 8 + QK_K // 32 + 4),
GGMLQuantizationType.IQ2_S: (256, 2 + QK_K // 4 + QK_K // 16),
GGMLQuantizationType.IQ4_XS: (256, 2 + 2 + QK_K // 2 + QK_K // 64),
} }