--- license: apache-2.0 base_model: allura-org/MN-12b-RP-Ink tags: - roleplay - conversational - llama-cpp - gguf-my-repo language: - en --- # Triangle104/MN-12b-RP-Ink-Q6_K-GGUF This model was converted to GGUF format from [`allura-org/MN-12b-RP-Ink`](https://huggingface.co/allura-org/MN-12b-RP-Ink) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/allura-org/MN-12b-RP-Ink) for more details on the model. --- Model details: - A roleplay-focused LoRA finetune of Mistral Nemo Instruct. Methodology and hyperparams inspired by SorcererLM and Slush. Renamed to Ink to distinguish from [insert every other rp tune ever], but it's the same data as was used in the Teleut RP model. Dataset The worst mix of data you've ever seen. Like, seriously, you do not want to see the things that went into this model. It's bad. "this is like washing down an adderall with a bottle of methylated rotgut" - inflatebot Quants Static GGUFs Recommended Settings Chat template: Mistral v3-Tekken Recommended samplers (not the be-all-end-all, try some on your own!): Temp 1.25 / MinP 0.1 Temp 1.03 / TopK 200 / MinP 0.05 / TopA 0.2 Hyperparams General Epochs = 2 LR = 6e-5 LR Scheduler = Cosine Optimizer = Paged AdamW 8bit Effective batch size = 12 LoRA Rank = 16 Alpha = 32 Dropout = 0.25 (Inspiration: Slush) Credits Humongous thanks to the people who created the data. I would credit you all, but that would be cheating ;) Big thanks to all Allura members, especially Toasty, for testing and emotional support ilya /platonic Also special thanks to Bot for making the model card image here :3 NO thanks to Infermatic. They suck at hosting models --- ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo Triangle104/MN-12b-RP-Ink-Q6_K-GGUF --hf-file mn-12b-rp-ink-q6_k.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Triangle104/MN-12b-RP-Ink-Q6_K-GGUF --hf-file mn-12b-rp-ink-q6_k.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo Triangle104/MN-12b-RP-Ink-Q6_K-GGUF --hf-file mn-12b-rp-ink-q6_k.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo Triangle104/MN-12b-RP-Ink-Q6_K-GGUF --hf-file mn-12b-rp-ink-q6_k.gguf -c 2048 ```