README.md · RobertSinclair/README at 56c77b35175bf5a8d7076bfb54d4c6b1b2862f5d

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title: README
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These are my own quantizations (updated almost daily).

The difference with normal quantizations is that I quantize the output and embed tensors to f16.
and the other tensors to 15_k,q6_k or q8_0.
This creates models that are little or not degraded at all and have a smaller size.
They run at about 3-6 t/sec on CPU only using llama.cpp
And obviously faster on computers with potent GPUs

ALL the models were quantized in this way:
quantize.exe --allow-requantize --output-tensor-type f16 --token-embedding-type f16 model.f16.gguf model.f16.q5.gguf q5_k
quantize.exe --allow-requantize --output-tensor-type f16 --token-embedding-type f16 model.f16.gguf model.f16.q6.gguf q6_k
quantize.exe --allow-requantize --output-tensor-type f16 --token-embedding-type f16 model.f16.gguf model.f16.q6.gguf q8_0
quantize.exe --allow-requantize --pure model.f16.gguf model.f16.q8_p.gguf q8_0
and there is also a pure f16 and a pure q8 in every directory.