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Model: GalrionSoftworks/MN-LooseCannon-12B-v1 Source: Original Platform
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README.md
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README.md
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---
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tags:
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- merge
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- mergekit
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- lazymergekit
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- aetherwiing/MN-12B-Starcannon-v3
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- Sao10K/MN-12B-Lyra-v1
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base_model:
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- aetherwiing/MN-12B-Starcannon-v3
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- Sao10K/MN-12B-Lyra-v1
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model-index:
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- name: MN-LooseCannon-12B-v1
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 54.18
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name: strict accuracy
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source:
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url: >-
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-v1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 29.98
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name: normalized accuracy
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source:
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url: >-
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-v1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 6.5
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name: exact match
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source:
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url: >-
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-v1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 4.7
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name: acc_norm
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source:
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url: >-
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-v1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 10.96
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name: acc_norm
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source:
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url: >-
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-v1
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 24.4
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name: accuracy
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source:
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url: >-
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https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=GalrionSoftworks/MN-LooseCannon-12B-v1
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name: Open LLM Leaderboard
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pipeline_tag: text-generation
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---
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# MN-LooseCannon-12B-v1
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MN-LooseCannon-12B-v1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [aetherwiing/MN-12B-Starcannon-v3](https://huggingface.co/aetherwiing/MN-12B-Starcannon-v3)
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* [Sao10K/MN-12B-Lyra-v1](https://huggingface.co/Sao10K/MN-12B-Lyra-v1)
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## 🧩 Configuration
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```yaml
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models:
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- model: aetherwiing/MN-12B-Starcannon-v3
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parameters:
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density: 0.3
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weight: 0.75
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- model: Sao10K/MN-12B-Lyra-v1
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parameters:
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density: 0.7
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weight: 0.25
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merge_method: ties
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base_model: aetherwiing/MN-12B-Starcannon-v3
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parameters:
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normalize: true
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dtype: bfloat16
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```
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## 💻 Usage
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```python
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!pip install -qU transformers accelerate
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from transformers import AutoTokenizer
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import transformers
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import torch
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model = "GalrionSoftworks/MN-LooseCannon-12B-v1"
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_GalrionSoftworks__MN-LooseCannon-12B-v1)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |21.78|
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|IFEval (0-Shot) |54.18|
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|BBH (3-Shot) |29.98|
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|MATH Lvl 5 (4-Shot)| 6.50|
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|GPQA (0-shot) | 4.70|
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|MuSR (0-shot) |10.96|
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|MMLU-PRO (5-shot) |24.40|
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