--- license: apache-2.0 datasets: - Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned - anthracite-org/stheno-filtered-v1.1 - PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT - Gryphe/Sonnet3.5-Charcard-Roleplay - Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned - anthracite-org/kalo-opus-instruct-22k-no-refusal - anthracite-org/nopm_claude_writing_fixed - anthracite-org/kalo_opus_misc_240827 language: - en - fr - de - es - it - pt - ru - zh - ja pipeline_tag: text-generation --- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64adfd277b5ff762771e4571/NGEOrcWYPDnFmvHinkXVk.png) 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. [full](https://huggingface.co/Epiculous/Azure_Dusk-v0.2) / [exl2](https://huggingface.co/Epiculous/Azure_Dusk-v0.2-exl2) / gguf ## Prompting The v0.2 models are trained on ChatML, the prompting structure goes a little something like this: ``` <|im_start|>user Hi there!<|im_end|> <|im_start|>assistant Nice to meet you!<|im_end|> <|im_start|>user Can I ask a question?<|im_end|> <|im_start|>assistant ``` ### Context and Instruct The v0.2 models are trained on ChatML, please use that Context and Instruct template. ### Current Top Sampler Settings [Spicy_Temp](https://files.catbox.moe/9npj0z.json)
[Violet_Twilight-Nitral-Special](https://files.catbox.moe/ot54u3.json)
## Training 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 RP data, the LoRA was then applied to base. Finally, the new modified base was trained 2 epochs on instruct, and the new instruct LoRA was applied to the modified base, resulting in what you see here. [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)