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README.md
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@@ -28,4 +28,4 @@ It was quantized using official svdquant toolset using both `fast` and `gptq` pr
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### P.S. Yields worse than expected generation results, so **not recommended as for now**, I will take another try to quantize it using slow mode.
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### P.P.S. I've ran full quantization, but due to the way the toolset implemented, it had a bug at the very end in the eval part of workflow, so it exited with error not saving a single byte of final quantization result, everything is lost.
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Due to the fact that I paid for the compute myself I consider this loss of ~$60 as a valuable lesson, but I would not redo it again, as I am short on free cash atm. Sorry. Fot those who willing to have it done - feel free to generate credit code at RunPod, and send it to me via telegram: [t.me/WaveCut](https://t.me/WaveCut), and I'll be happy to get another shot at it.
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| 28 |
### P.S. Yields worse than expected generation results, so **not recommended as for now**, I will take another try to quantize it using slow mode.
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| 29 |
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| 30 |
### P.P.S. I've ran full quantization, but due to the way the toolset implemented, it had a bug at the very end in the eval part of workflow, so it exited with error not saving a single byte of final quantization result, everything is lost.
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Due to the fact that I paid for the compute myself I consider this loss of ~$60 as a valuable lesson, but I would not redo it again, as I am short on free cash atm. Sorry. Fot those who willing to have it done - feel free to generate a redeemable credit code at RunPod, and send it to me via telegram: [t.me/WaveCut](https://t.me/WaveCut), and I'll be happy to get another shot at it.
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