Text Generation
GGUF
English
creative
creative writing
fiction writing
plot generation
sub-plot generation
story generation
scene continue
storytelling
fiction story
science fiction
romance
all genres
story
writing
vivid prosing
vivid writing
fiction
roleplaying
bfloat16
swearing
rp
horror
mistral nemo
mergekit
Not-For-All-Audiences
Inference Endpoints
Update README.md
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README.md
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@@ -78,10 +78,14 @@ This super merge captures the attibutes of all these top models and makes them e
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- Emotional connections.
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- Prose quality
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This super merge is also super stable, and runs with all parameters and settings.
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10 versions of this model will be released, this is release #1 - "part 1".
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Usually I release one or two versions from the "best of the lot", however in this case all
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of the versions turned out so well - all with their own quirks and character - that I will be
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releasing all 10.
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(examples generations below)
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Model may produce NSFW content :
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Swearing, horror, graphic horror, distressing scenes, etc etc.
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This model has an INTENSE action bias, with a knack for cliffhangers and surprises.
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[ https://huggingface.co/nothingiisreal/MN-12B-Celeste-V1.9 ]
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<h3>EXAMPLES PROMPTS and OUTPUT:</h3>
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- Emotional connections.
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- Prose quality
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This super merge is also super stable (a hairs breath from Mistral Nemo's ppl), and runs with all parameters and settings.
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10 versions of this model will be released, this is release #1 - "part 1".
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<B>Kiss of Madness?</B>
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See the 2nd last example below, this is when the model earned its name.
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Usually I release one or two versions from the "best of the lot", however in this case all
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of the versions turned out so well - all with their own quirks and character - that I will be
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releasing all 10.
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(examples generations below)
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Model may produce NSFW content : Swearing, horror, graphic horror, distressing scenes, etc etc.
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This model has an INTENSE action bias, with a knack for cliffhangers and surprises.
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[ https://huggingface.co/nothingiisreal/MN-12B-Celeste-V1.9 ]
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This is a four step merge (3 pass-throughs => "Fine-Tune" / "Instruct") then "mated" using "DARE-TIES".
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In involves these three models:
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[ https://huggingface.co/DavidAU/MN-18.5B-Celeste-V1.9-Story-Wizard-ED1-Instruct-GGUF ]
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[ https://huggingface.co/DavidAU/MN-Magnum-v2.5-18.5B-kto-Story-Wizard-ED1-Instruct-GGUF ]
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[ https://huggingface.co/DavidAU/MN-Rocinante-18.5B-v1.1-Story-Wizard-ED1-Instruct-GGUF ]
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Combined as follows using "MERGEKIT":
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<PRE>
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models:
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- model: E:/MN-Rocinante-18.5B-v1.1-Instruct
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- model: E:/MN-magnum-v2.5-12b-kto-Instruct
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parameters:
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weight: .6
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density: .8
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- model: E:/MN-18.5B-Celeste-V1.9-Instruct
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parameters:
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weight: .38
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density: .6
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merge_method: dare_ties
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tokenizer_source: union
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base_model: E:/MN-Rocinante-18.5B-v1.1-Instruct
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dtype: bfloat16
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</PRE>
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Special Notes:
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Due to how DARE-TIES works, everytime you run this merge you will get a slightly different model.
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This is due to "random" pruning method in "DARE-TIES".
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Mistral Nemo models used here seem acutely sensitive to this process.
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"tokenizer_source: union" is used so that multiple "templates" work and each fine tune uses one or two of the templates.
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<h3>EXAMPLES PROMPTS and OUTPUT:</h3>
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