---
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-Q4_K_M-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-Q4_K_M-GGUF --hf-file mahou-1.5-mistral-nemo-12b-q4_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Mahou-1.5-mistral-nemo-12B-Q4_K_M-GGUF --hf-file mahou-1.5-mistral-nemo-12b-q4_k_m.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-Q4_K_M-GGUF --hf-file mahou-1.5-mistral-nemo-12b-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Mahou-1.5-mistral-nemo-12B-Q4_K_M-GGUF --hf-file mahou-1.5-mistral-nemo-12b-q4_k_m.gguf -c 2048
```