Triangle104
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README.md
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This model was converted to GGUF format from [`DoppelReflEx/MN-12B-Mimicore-WhiteSnake`](https://huggingface.co/DoppelReflEx/MN-12B-Mimicore-WhiteSnake) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/DoppelReflEx/MN-12B-Mimicore-WhiteSnake) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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This model was converted to GGUF format from [`DoppelReflEx/MN-12B-Mimicore-WhiteSnake`](https://huggingface.co/DoppelReflEx/MN-12B-Mimicore-WhiteSnake) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/DoppelReflEx/MN-12B-Mimicore-WhiteSnake) for more details on the model.
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---
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Model details:
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Better version of GreenSnake, not too much different in OpenLLM
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LeaderBoard scores. Merge with
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cgato/Nemo-12b-Humanize-KTO-Experimental-Latest so this model could
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perform 'human response'.
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This merge model is a gift for Lunar New Year, haha. Enjoy it.
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Good for RP, ERP, Story Telling.
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PS: It's don't have cgato/Nemo-12b-Humanize-KTO-Experimental-Latest Tokenization issue.
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Update: Still have cgato/Nemo-12b-Humanize-KTO-Experimental-Latest
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Tokenization issue, but randomly occur in rare rate. If you are
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experiencing this issue, just press re-generate to reroll other
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message/response.
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Chat Format? ChatML of course!
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Models Merged
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The following models were included in the merge:
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cgato/Nemo-12b-Humanize-KTO-Experimental-Latest
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DoppelReflEx/MN-12B-Mimicore-GreenSnake
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Configuration
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The following YAML configuration was used to produce this model:
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models:
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- model: cgato/Nemo-12b-Humanize-KTO-Experimental-Latest
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parameters:
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density: 0.9
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weight: 1
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- model: DoppelReflEx/MN-12B-Mimicore-GreenSnake
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parameters:
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density: 0.6
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weight: 0.8
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merge_method: dare_ties
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base_model: IntervitensInc/Mistral-Nemo-Base-2407-chatml
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tokenizer_source: base
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---
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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