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README.md
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## There's some kind of gguf tokenization issue where its not properly handling the <|im_end|> EOS token and instead breaks it into multiple smaller ones which degrades performance for gguf users. Need to submit an issue ticket. Unsure if this impacts other quantization formats.
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## If possible, please use the safetensors or Exllama2 for best performance. Exllama2 tokenizes correctly.
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This is the first public release of the Humanize model I've been working on. That way folks have a stable repo to download from and can expect some consistient level of performance when downloading.
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## Goals
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The goal of this model is to make something that feels different from other models out there. I wanted to accomplish this in two ways, first use as little synthetic data as possible, and second, by hand judging KTO samples to avoid common AI phrases and repetition. It has seen very very little synthetic data and without RL is unusable. The RL dataset was built by pulling responses from the model itself and then having a human (me) review each response.
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## There's some kind of gguf tokenization issue where its not properly handling the <|im_end|> EOS token and instead breaks it into multiple smaller ones which degrades performance for gguf users. Need to submit an issue ticket. Unsure if this impacts other quantization formats.
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## If possible, please use the safetensors or Exllama2 for best performance. Exllama2 tokenizes correctly.
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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This is the first public release of the Humanize model I've been working on. That way folks have a stable repo to download from and can expect some consistient level of performance when downloading.
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## Goals
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The goal of this model is to make something that feels different from other models out there. I wanted to accomplish this in two ways, first use as little synthetic data as possible, and second, by hand judging KTO samples to avoid common AI phrases and repetition. It has seen very very little synthetic data and without RL is unusable. The RL dataset was built by pulling responses from the model itself and then having a human (me) review each response.
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