---
base_model:
- Sao10K/L3-8B-Lunaris-v1
- merge
- mergekit
- lazymergekit
model-index:
- name: L3-12B-Lunaris-v1
  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: 69.09
      name: strict accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tremontaine/L3-12B-Lunaris-v1
      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: 32.18
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tremontaine/L3-12B-Lunaris-v1
      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: 8.16
      name: exact match
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tremontaine/L3-12B-Lunaris-v1
      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: 7.94
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tremontaine/L3-12B-Lunaris-v1
      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: 4.05
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tremontaine/L3-12B-Lunaris-v1
      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: 30.83
      name: accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tremontaine/L3-12B-Lunaris-v1
      name: Open LLM Leaderboard
---

# L3-12B-Lunaris-v1

L3-12B-Lunaris-v1 is a self merge of the following model using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing) with --clone-tensors argument added:
* [Sao10K/L3-8B-Lunaris-v1](https://huggingface.co./Sao10K/L3-8B-Lunaris-v1)

Works best with lower temperature, between 0.8-0.9.

## 🧩 Configuration

```yaml
dtype: bfloat16
merge_method: passthrough
slices:
- sources:
  - layer_range: [0, 8]
    model: Sao10K/L3-8B-Lunaris-v1
    parameters:
      scale_rules:
      - filter: value
        value: 0.8
- sources:
  - layer_range: [8, 16]
    model: Sao10K/L3-8B-Lunaris-v1
    parameters:
      scale_rules:
      - filter: value
        value: 0.8
- sources:
  - layer_range: [16, 24]
    model: Sao10K/L3-8B-Lunaris-v1
    parameters:
      scale_rules:
      - filter: value
        value: 1.0
- sources:
  - layer_range: [24, 32]
    model: Sao10K/L3-8B-Lunaris-v1
    parameters:
      scale_rules:
      - filter: value
        value: 1.0
- sources:
  - layer_range: [0, 8]
    model: Sao10K/L3-8B-Lunaris-v1
    parameters:
      scale_rules:
      - filter: value
        value: 0.7
- sources:
  - layer_range: [8, 16]
    model: Sao10K/L3-8B-Lunaris-v1
    parameters:
      scale_rules:
      - filter: value
        value: 0.7
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Tremontaine/L3-12B-Lunaris-v1"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_Tremontaine__L3-12B-Lunaris-v1)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |25.38|
|IFEval (0-Shot)    |69.09|
|BBH (3-Shot)       |32.18|
|MATH Lvl 5 (4-Shot)| 8.16|
|GPQA (0-shot)      | 7.94|
|MuSR (0-shot)      | 4.05|
|MMLU-PRO (5-shot)  |30.83|