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README.md
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@@ -39,6 +39,9 @@ If you are using GGUF I strongly advise using ChatML, for some reason that quant
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[Crimson_Dawn-Nitral-Special](https://files.catbox.moe/8xjxht.json) - Considered the best settings! <br/>
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[Crimson_Dawn-Magnum-Style](https://files.catbox.moe/lc59dn.json)
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## Training
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Training was done twice over 2 epochs each on two 2x [NVIDIA A6000 GPUs](https://www.nvidia.com/en-us/design-visualization/rtx-a6000/) using LoRA. A two-phased approach was used in which the base model was trained 2 epochs on Instruct data, the LoRA was then applied to base. Finally, the new modified base was trained 2 epochs on RP, and the new RP LoRA was applied to the modified base, resulting in what you see here.
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[Crimson_Dawn-Nitral-Special](https://files.catbox.moe/8xjxht.json) - Considered the best settings! <br/>
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[Crimson_Dawn-Magnum-Style](https://files.catbox.moe/lc59dn.json)
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### Tokenizer
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If you are using SillyTavern, please set the tokenizer to API (WebUI/ koboldcpp)
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## Training
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Training was done twice over 2 epochs each on two 2x [NVIDIA A6000 GPUs](https://www.nvidia.com/en-us/design-visualization/rtx-a6000/) using LoRA. A two-phased approach was used in which the base model was trained 2 epochs on Instruct data, the LoRA was then applied to base. Finally, the new modified base was trained 2 epochs on RP, and the new RP LoRA was applied to the modified base, resulting in what you see here.
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