README.md

---
base_model: flammenai/Mahou-1.5-mistral-nemo-12B
datasets:
- flammenai/MahouMix-v1
library_name: transformers
license: apache-2.0
tags:
- llama-cpp
- gguf-my-repo
model-index:
- name: Mahou-1.5-mistral-nemo-12B
 results:
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: IFEval (0-Shot)
 type: HuggingFaceH4/ifeval
 args:
 num_few_shot: 0
 metrics:
 - type: inst_level_strict_acc and prompt_level_strict_acc
 value: 67.51
 name: strict accuracy
 source:
 url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=flammenai/Mahou-1.5-mistral-nemo-12B
 name: Open LLM Leaderboard
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: BBH (3-Shot)
 type: BBH
 args:
 num_few_shot: 3
 metrics:
 - type: acc_norm
 value: 36.26
 name: normalized accuracy
 source:
 url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=flammenai/Mahou-1.5-mistral-nemo-12B
 name: Open LLM Leaderboard
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: MATH Lvl 5 (4-Shot)
 type: hendrycks/competition_math
 args:
 num_few_shot: 4
 metrics:
 - type: exact_match
 value: 5.06
 name: exact match
 source:
 url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=flammenai/Mahou-1.5-mistral-nemo-12B
 name: Open LLM Leaderboard
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: GPQA (0-shot)
 type: Idavidrein/gpqa
 args:
 num_few_shot: 0
 metrics:
 - type: acc_norm
 value: 3.47
 name: acc_norm
 source:
 url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=flammenai/Mahou-1.5-mistral-nemo-12B
 name: Open LLM Leaderboard
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: MuSR (0-shot)
 type: TAUR-Lab/MuSR
 args:
 num_few_shot: 0
 metrics:
 - type: acc_norm
 value: 16.47
 name: acc_norm
 source:
 url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=flammenai/Mahou-1.5-mistral-nemo-12B
 name: Open LLM Leaderboard
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: MMLU-PRO (5-shot)
 type: TIGER-Lab/MMLU-Pro
 config: main
 split: test
 args:
 num_few_shot: 5
 metrics:
 - type: acc
 value: 28.91
 name: accuracy
 source:
 url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=flammenai/Mahou-1.5-mistral-nemo-12B
 name: Open LLM Leaderboard
---

# Triangle104/Mahou-1.5-mistral-nemo-12B-Q5_K_S-GGUF
This model was converted to GGUF format from [`flammenai/Mahou-1.5-mistral-nemo-12B`](https://huggingface.co/flammenai/Mahou-1.5-mistral-nemo-12B) 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/flammenai/Mahou-1.5-mistral-nemo-12B) for more details on the model.

---
Model details:
-
Mahou-1.5-mistral-nemo-12B

Mahou is designed to provide short messages in a conversational context. It is capable of casual conversation and character roleplay.
Chat Format

This model has been trained to use ChatML format.

<|im_start|>system
{{system}}<|im_end|>
<|im_start|>{{char}}
{{message}}<|im_end|>
<|im_start|>{{user}}
{{message}}<|im_end|>

Roleplay Format

 Speech without quotes.
 Actions in *asterisks*

*leans against wall cooly* so like, i just casted a super strong spell at magician academy today, not gonna lie, felt badass.

SillyTavern Settings

 Use ChatML for the Context Template.
 Enable Instruct Mode.
 Use the Mahou ChatML Instruct preset.
 Use the Mahou Sampler preset.

Method

ORPO finetuned with 4x H100 for 3 epochs.
Open LLM Leaderboard Evaluation Results

Detailed results can be found here
Metric Value
Avg. 26.28
IFEval (0-Shot) 67.51
BBH (3-Shot) 36.26
MATH Lvl 5 (4-Shot) 5.06
GPQA (0-shot) 3.47
MuSR (0-shot) 16.47
MMLU-PRO (5-shot) 28.91

---

## 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/Mahou-1.5-mistral-nemo-12B-Q5_K_S-GGUF --hf-file mahou-1.5-mistral-nemo-12b-q5_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Mahou-1.5-mistral-nemo-12B-Q5_K_S-GGUF --hf-file mahou-1.5-mistral-nemo-12b-q5_k_s.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/Mahou-1.5-mistral-nemo-12B-Q5_K_S-GGUF --hf-file mahou-1.5-mistral-nemo-12b-q5_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Mahou-1.5-mistral-nemo-12B-Q5_K_S-GGUF --hf-file mahou-1.5-mistral-nemo-12b-q5_k_s.gguf -c 2048
```