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Following up on Crimson_Dawn-v0.2 we have Azure_Dusk-v0.2! Training on [Mistral-Nemo-Base-2407](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407) this time I've added significantly more data, as well as trained using RSLoRA as opposed to regular LoRA. Another key change is training on ChatML as opposed to Mistral Formatting.
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# Quants!
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<strong>full</strong> / [exl2](https://huggingface.co/Epiculous/Azure_Dusk-v0.2-exl2) / [gguf]()
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## Prompting
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The v0.2 models are trained on ChatML, the prompting structure goes a little something like this:
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Following up on Crimson_Dawn-v0.2 we have Azure_Dusk-v0.2! Training on [Mistral-Nemo-Base-2407](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407) this time I've added significantly more data, as well as trained using RSLoRA as opposed to regular LoRA. Another key change is training on ChatML as opposed to Mistral Formatting.
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# Quants!
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<strong>full</strong> / [exl2](https://huggingface.co/Epiculous/Azure_Dusk-v0.2-exl2) / [gguf](https://huggingface.co/Epiculous/Azure_Dusk-v0.2-GGUF)
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## Prompting
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The v0.2 models are trained on ChatML, the prompting structure goes a little something like this:
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