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+ ---
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+ tags:
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+ - manticore
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+ - guanaco
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+ - uncensored
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+
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+ ---
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+ ---
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+ # 4bit GGML of:
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+ Manticore-13b-Chat-Pyg by [openaccess-ai-collective](https://huggingface.co/openaccess-ai-collective/manticore-13b-chat-pyg) with the Guanaco 13b qLoRa by [TimDettmers](https://huggingface.co/timdettmers/guanaco-13b) applied through [Monero](https://huggingface.co/Monero/Manticore-13b-Chat-Pyg-Guanaco), quantized by [mindrage](https://huggingface.co/mindrage), uncensored
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+ [link to GPTQ Version](https://huggingface.co/mindrage/Manticore-13B-Chat-Pyg-Guanaco-GPTQ-4bit-128g.no-act-order.safetensors)
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+ ---
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+ Quantized to 4bit GGML (4_0) using the newest llama.cpp and will therefore only work with llama.cpp versions compiled after May 19th, 2023.
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+ The model seems to have noticeably benefited from further augmentation with the Guanaco qLora.
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+ Its capabilities seem broad, even compared with other Wizard or Manticore models, with expected weaknesses at coding. It is very good at in-context-learning and (in its class) reasoning.
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+ It both follows instructions well, and can be used as a chatbot.
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+ Refreshingly, it does not seem to insist on aggressively sticking to narratives to justify formerly hallucinated output as much as similar models. It's output seems... eerily smart at times.
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+ I believe the model is fully unrestricted/uncensored and will generally not berate.
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+ ---
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+ Prompting style + settings:
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+ ---
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+ Presumably due to the very diverse training-data the model accepts a variety of prompting styles with relatively few issues, including the ###-Variant, but seems to work best using:
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+ # "Naming" the model works great by simply modifying the context. Substantial changes in its behaviour can be caused very simply by appending to "ASSISTANT:", like "ASSISTANT: After careful consideration, thinking step-by-step, my response is:"
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+
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+ user: "USER:" -
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+ bot: "ASSISTANT:" -
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+ context: "This is a conversation between an advanced AI and a human user."
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+
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+ Turn Template: <|user|> <|user-message|>\n<|bot|><|bot-message|>\n
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+ Settings that work well without (subjectively) being too deterministic:
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+ temp: 0.15 -
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+ top_p: 0.1 -
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+ top_k: 40 -
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+ rep penalty: 1.1
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+ ---