--- tags: - merge - mergekit - lazymergekit - aetherwiing/MN-12B-Starcannon-v3 - Sao10K/MN-12B-Lyra-v1 base_model: - aetherwiing/MN-12B-Starcannon-v3 - Sao10K/MN-12B-Lyra-v1 model-index: - name: MN-LooseCannon-12B-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: 54.18 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-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: 29.98 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-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: 6.5 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-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: 4.7 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-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: 10.96 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-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: 24.4 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-v1 name: Open LLM Leaderboard --- # MN-LooseCannon-12B-v1 MN-LooseCannon-12B-v1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [aetherwiing/MN-12B-Starcannon-v3](https://huggingface.co/aetherwiing/MN-12B-Starcannon-v3) * [Sao10K/MN-12B-Lyra-v1](https://huggingface.co/Sao10K/MN-12B-Lyra-v1) ## 🧩 Configuration ```yaml models: - model: aetherwiing/MN-12B-Starcannon-v3 parameters: density: 0.3 weight: 0.75 - model: Sao10K/MN-12B-Lyra-v1 parameters: density: 0.7 weight: 0.25 merge_method: ties base_model: aetherwiing/MN-12B-Starcannon-v3 parameters: normalize: true dtype: bfloat16 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "GalrionSoftworks/MN-LooseCannon-12B-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_GalrionSoftworks__MN-LooseCannon-12B-v1) | Metric |Value| |-------------------|----:| |Avg. |21.78| |IFEval (0-Shot) |54.18| |BBH (3-Shot) |29.98| |MATH Lvl 5 (4-Shot)| 6.50| |GPQA (0-shot) | 4.70| |MuSR (0-shot) |10.96| |MMLU-PRO (5-shot) |24.40|