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This merge, this time grounded in Gemma2 9B Instruct fine-tunes, is another demonstration that models without any fine-tuning to support roleplay can still perform the function, maintaining coherence and attention to context. It should be evident that no overt fine-tuning is required for roleplay in text generation; pretraining should provide models with a requisite basic understanding of the world, so all that should be needed is some corrective fine-tuning to address observed defects in portraying the world along with datasets to promote a suitably entertaining writing style. Good Instruct tuning should promote reasoning, coherence, and attention to context.
This merge, this time grounded in Gemma2 9B Instruct fine-tunes, is another demonstration that models without any fine-tuning to support roleplay can still perform the function, maintaining coherence and attention to context. It should be evident that no overt fine-tuning is required for roleplay in text generation; pretraining should provide models with a requisite basic understanding of the world, so all that should be needed is some corrective fine-tuning to address observed defects in portraying the world along with datasets to promote a suitably entertaining writing style. Good Instruct tuning should promote reasoning, coherence, and attention to context.
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resource
https://huggingface.co/grimjim/Kitsunebi-v1-Gemma2-8k-9B
model
grimjim/Kitsunebi-v1-Gemma2-8k-9B
https://huggingface.co/grimjim/Kitsunebi-v1-Gemma2-8k-9B
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resource
https://huggingface.co/grimjim/Kitsunebi-v1-Gemma2-8k-9B-GGUF
model
grimjim/Kitsunebi-v1-Gemma2-8k-9B-GGUF
https://huggingface.co/grimjim/Kitsunebi-v1-Gemma2-8k-9B-GGUF
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I opted not to incorporate the UCLA SPPO fine-tune for Gemma2 9B after observing context confusion occur with some frequency during complex scenarios.
I opted not to incorporate the UCLA SPPO fine-tune for Gemma2 9B after observing context confusion occur with some frequency during complex scenarios.
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Thanks to Axcxept co., ltd. for fine-tuning HODACHI/EZO-Common-9B-gemma-2-it, and to Princeton NLP Group for fine-tuning princeton-nlp/gemma-2-9b-it-SimPO.
Thanks to Axcxept co., ltd. for fine-tuning HODACHI/EZO-Common-9B-gemma-2-it, and to Princeton NLP Group for fine-tuning princeton-nlp/gemma-2-9b-it-SimPO.
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resource
https://huggingface.co/AXCXEPT/EZO-Common-9B-gemma-2-it
model
AXCXEPT/EZO-Common-9B-gemma-2-it
https://huggingface.co/AXCXEPT/EZO-Common-9B-gemma-2-it
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resource
https://huggingface.co/princeton-nlp/gemma-2-9b-it-SimPO
model
princeton-nlp/gemma-2-9b-it-SimPO
https://huggingface.co/princeton-nlp/gemma-2-9b-it-SimPO
This merge, this time grounded in Gemma2 9B Instruct fine-tunes, is another demonstration that models without any fine-tuning to support roleplay can still perform the function, maintaining coherence and attention to context. It should be evident that no overt fine-tuning is required for roleplay in text generation; pretraining should provide models with a requisite basic understanding of the world, so all that should be needed is some corrective fine-tuning to address observed defects in portraying the world along with datasets to promote a suitably entertaining writing style. Good Instruct tuning should promote reasoning, coherence, and attention to context.
https://huggingface.co/grimjim/Kitsunebi-v1-Gemma2-8k-9B
https://huggingface.co/grimjim/Kitsunebi-v1-Gemma2-8k-9B-GGUF

I opted not to incorporate the UCLA SPPO fine-tune for Gemma2 9B after observing context confusion occur with some frequency during complex scenarios.

Thanks to Axcxept co., ltd. for fine-tuning HODACHI/EZO-Common-9B-gemma-2-it, and to Princeton NLP Group for fine-tuning princeton-nlp/gemma-2-9b-it-SimPO.
https://huggingface.co/AXCXEPT/EZO-Common-9B-gemma-2-it
https://huggingface.co/princeton-nlp/gemma-2-9b-it-SimPO
👍
John6666 djuna prithivMLmods