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Specialized uncensored quants for new OpenAI 20B MOE - Mixture of Experts Model at 80+ T/S. See settings and special instructions for using UNCENSORED (refusals removed AND "nanny be gone") models below. "HERETIC" method results in a model devoid of refusals, and without brain damage too. (see below) NEO, Horror and NEOCode dataset improves overall performance, and are for all use cases. This model uses "P-E-W"'s model as a base which DE-CENSORS the model and removes refusals.

Text generation
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This is a Floating Point 32 upscale, where all components and merges were remastered to floating point 32. This includes all the merges (recreated with master files), and where possible subbing full FP32 models. This repo contains the new Imatrix Plus 2 quants using a new inhouse dataset merged with a master dataset to push performance of the Ultra Quality remaster even higher. At Q2K an impressive drop of 533 points in perplexity. (lower is better) (VS: Q2K original base model: PPL = 9.8077 +/- 0.06821 )

Text generation
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This is a Floating Point 32 upscale, where all components and merges were remastered to floating point 32. This includes all the merges (recreated with master files), and where possible subbing full FP32 models. At Q2K an impressive drop of 533 points in perplexity. (lower is better) (VS: Q2K original base model: PPL = 9.8077 +/- 0.06821 ) At Q4KM a whopping drop of 976 points in perplexity. (VS: Q4km original base model -> PPL = 8.7858 +/- 0.06074)

Text generation
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Special note: All quants of this model can be used on GPU and/or CPU/RAM only due to unique construction of the model. There are also several versions of quant sizes with special features too. GGUF NEO Imatrix ggufs of Qwen's new "Qwen3-30B-A3B" Mixture of experts model, extended to 128k (131072) (up from 32k/32768) context as per Qwen tech notes using "YARN". NEO Imatrix dataset was developed in house after testing and evaluating over 50 Imatrix datasets and a lot of "tinkering".

Text generation
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