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+ ---
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+ license: other
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+ language:
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+ - en
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+ pipeline_tag: text-generation
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+ inference: false
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+ tags:
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+ - transformers
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+ - gguf
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+ - imatrix
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+ - Silicon-Maid-7B
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+ ---
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+ Quantizations of https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B
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+
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+ ### Experiment
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+
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+ Quants **ending in "_X"** are experimental quants. These quants are the same as normal quants, but their token embedding weights are set to Q8_0 except for Q6_K and Q8_0 which are set to F16. The change will make these experimental quants larger but in theory, should result in improved performance.
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+
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+ List of experimental quants:
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+ * Q2_K_X
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+ * Q4_K_M_X
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+ * Q5_K_M_X
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+ * Q6_K_X
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+ * Q8_0_X
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+
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+ ---
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+
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+ ### Inference Clients/UIs
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+ * [llama.cpp](https://github.com/ggerganov/llama.cpp)
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+ * [JanAI](https://github.com/janhq/jan)
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+ * [KoboldCPP](https://github.com/LostRuins/koboldcpp)
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+ * [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
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+ * [ollama](https://github.com/ollama/ollama)
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+ * [exllamav2](https://github.com/turboderp/exllamav2)
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+
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+ ---
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+
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+ # From original readme
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+
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+ Silicon-Maid-7B is another model targeted at being both strong at RP **and** being a smart cookie that can follow character cards very well. As of right now, Silicon-Maid-7B outscores both of my previous 7B RP models in my RP benchmark and I have been impressed by this model's creativity. It is suitable for RP/ERP and general use.
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+
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+ ### Prompt Template (Alpaca)
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+ I found the best SillyTavern results from using the Noromaid template but please try other templates! Let me know if you find anything good.
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+
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+ SillyTavern config files: [Context](https://files.catbox.moe/ifmhai.json), [Instruct](https://files.catbox.moe/ttw1l9.json).
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+
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+ Additionally, here is my highly recommended [Text Completion preset](https://huggingface.co/SanjiWatsuki/Loyal-Macaroni-Maid-7B/blob/main/Characters/MinP.json). You can tweak this by adjusting temperature up or dropping min p to boost creativity or raise min p to increase stability. You shouldn't need to touch anything else!
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+
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+ ```
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+ Below is an instruction that describes a task. Write a response that appropriately completes the request.
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+
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+ ### Instruction:
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+ {prompt}
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+
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+ ### Response:
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+ ```