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Updated Tensor Encoding Schemes (markdown)

Brian 2024-05-17 16:51:05 +10:00
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Tensor-Encoding-Schemes.md

@ -56,3 +56,4 @@ This is not definitive, but is helpful when reading sourcecode or console output
| IQ4_NL | GGML_FTYPE_MOSTLY_IQ4_NL | GGML_TYPE_IQ4_NL | 4.5 | i-quantization | Superblocks with 16 blocks, each block has 16 weights | w = [non linear mapping of quants to weights] | [llama.cpp PR: IQ4_NL: 4-bit non-linear quants with blocks of 32 #5590](https://github.com/ggerganov/llama.cpp/pull/5590) | | IQ4_NL | GGML_FTYPE_MOSTLY_IQ4_NL | GGML_TYPE_IQ4_NL | 4.5 | i-quantization | Superblocks with 16 blocks, each block has 16 weights | w = [non linear mapping of quants to weights] | [llama.cpp PR: IQ4_NL: 4-bit non-linear quants with blocks of 32 #5590](https://github.com/ggerganov/llama.cpp/pull/5590) |
| IQ4_XS | GGML_FTYPE_MOSTLY_IQ4_XS | GGML_TYPE_IQ4_XS | 4.25 | i-quantization | Superblocks with 8 blocks, each block has 32 weights | w = func(superblock_scale, importance_matrix) | [llama.cpp PR: IQ4_XS: a 4.25 bpw quantization #5747](https://github.com/ggerganov/llama.cpp/pull/5747) | | IQ4_XS | GGML_FTYPE_MOSTLY_IQ4_XS | GGML_TYPE_IQ4_XS | 4.25 | i-quantization | Superblocks with 8 blocks, each block has 32 weights | w = func(superblock_scale, importance_matrix) | [llama.cpp PR: IQ4_XS: a 4.25 bpw quantization #5747](https://github.com/ggerganov/llama.cpp/pull/5747) |
* All superblocks have fp16 scaling factor and contains up to 256 weights. Number of weights in a block must be divisible by 256. (To be confirmed)