Triangle104/Bigger-Body-8b-Q4_K_S-GGUF

This model was converted to GGUF format from allura-org/Bigger-Body-8b using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

---

A roleplay-focused pseudo full-finetune of Ministral Instruct 2410. The successor to the Ink series.

Dataset

The Bigger Body (referred to as Ink v2.1, because that's still the internal name) mix is absolutely disgusting. It's even more cursed than the original Ink mix.

(Public) Original Datasets

-Fizzarolli/limarp-processed

-Norquinal/OpenCAI - two_users split

-allura-org/Celeste1.x-data-mixture

-mapsila/PIPPA-ShareGPT-formatted-named

allenai/tulu-3-sft-personas-instruction-following

-readmehay/medical-01-reasoning-SFT-json

-LooksJuicy/ruozhiba

-shibing624/roleplay-zh-sharegpt-gpt4-data

-CausalLM/Retrieval-SFT-Chat

-ToastyPigeon/fujin-filtered-instruct

Recommended Settings

Chat template: Mistral v7-tekken (NOT v3-tekken !!!! the main difference is that v7 has specific [SYSTEM_PROMPT] and [/SYSTEM_PROMPT] tags) Recommended samplers (not the be-all-end-all, try some on your own!):

I have literally no idea. you're on your own.

Hyperparams

General

Epochs = 2 LR = 2e-6 LR Scheduler = Cosine Optimizer = Apollo-mini Optimizer target modules = all_linear Effective batch size = 16 Weight Decay = 0.01 Warmup steps = 50 Total steps = 920

Credits

Humongous thanks to the people who created the data. Big thanks to all Allura members for testing and emotional support ilya /platonic

---

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Triangle104/Bigger-Body-8b-Q4_K_S-GGUF --hf-file bigger-body-8b-q4_k_s.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Bigger-Body-8b-Q4_K_S-GGUF --hf-file bigger-body-8b-q4_k_s.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps 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/Bigger-Body-8b-Q4_K_S-GGUF --hf-file bigger-body-8b-q4_k_s.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/Bigger-Body-8b-Q4_K_S-GGUF --hf-file bigger-body-8b-q4_k_s.gguf -c 2048