---
license: other
license_name: mrl
language:
- en
- zh
base_model: allura-org/Bigger-Body-8b
library_name: transformers
tags:
- axolotl
- roleplay
- conversational
- chat
- llama-cpp
- gguf-my-repo
---

# Triangle104/Bigger-Body-8b-Q8_0-GGUF
This model was converted to GGUF format from [`allura-org/Bigger-Body-8b`](https://huggingface.co/allura-org/Bigger-Body-8b) 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/Bigger-Body-8b) 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)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo Triangle104/Bigger-Body-8b-Q8_0-GGUF --hf-file bigger-body-8b-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Bigger-Body-8b-Q8_0-GGUF --hf-file bigger-body-8b-q8_0.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/Bigger-Body-8b-Q8_0-GGUF --hf-file bigger-body-8b-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Bigger-Body-8b-Q8_0-GGUF --hf-file bigger-body-8b-q8_0.gguf -c 2048
```