Not-For-All-Audiences
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README.md
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---
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license: cc-by-nc-2.0
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tags:
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- not-for-all-audiences
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---
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```
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"88 88" "88 88" "88 888 888 888 888
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b
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PROUDLY PRESENTS
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```
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# MN-12B-Tarsus-exl2-longcal
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Quantized using 115 rows of 8192 tokens from the default ExLlamav2-calibration dataset.
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Branches:
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- `main` -- `measurement.json`
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- `8b8h` -- 8bpw, 8bit lm_head
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- `6b6h` -- 6bpw, 6bit lm_head
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- `4b6h` -- 4bpw, 6bit lm_head
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- `3b6h` -- 3bpw, 6bit lm_head
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- `2.25b6h` -- 2.25bpw, 6bit lm_head
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Original model link: [Envoid/MN-12B-Tarsus](https://huggingface.co/Envoid/MN-12B-Tarsus)
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Original model README below.
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-----
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## CAUTION: This model was finetuned on a corpus that includes adult content and may produce mature content without warning.
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# MN-12B-Tarsus
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Is a full-weight finetune of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)
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Which underwent several intermediate steps.
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This finetune was made with chatting/roleplaying via SillyTavern in mind and thus all of the testing was done there, with the goals being to:
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-Reduce shiver-slop
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-Make the model more conversationally proactive
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-Give it a more human-like output (i.e. less gratuitous purple prose)
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-Reducing overall positivity bias
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It still responds well to Mistral-Instruct formatting.
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The results are imperfect and its assistant capabilities suffered somewhat as a result but in quick testing it definitely seems to have achieved all of the goals to varying degrees.
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It sometimes fumbles with tokens in odd places so it's certainly not perfect. Possibly best used as merge-fodder.
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Trained using [qlora-pipe](https://github.com/tdrussell/qlora-pipe)
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