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--- |
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license: cc-by-nc-4.0 |
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tags: |
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- merge |
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- mergekit |
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- lazymergekit |
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base_model: |
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- mlabonne/OmniTruthyBeagle-7B-v0 |
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- mlabonne/NeuBeagle-7B |
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- mlabonne/NeuralOmniBeagle-7B |
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model-index: |
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- name: Monarch-7B |
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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: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 73.04 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B |
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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: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 89.03 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B |
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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 (5-Shot) |
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type: cais/mmlu |
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config: all |
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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: 64.41 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B |
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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: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 77.35 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B |
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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: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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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: 84.61 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B |
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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: GSM8k (5-shot) |
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type: gsm8k |
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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: 69.07 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B |
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name: Open LLM Leaderboard |
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--- |
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# Monarch-7B |
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**Update 13/02/24: Monarch-7B is the best-performing model on the YALL leaderboard.** |
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Monarch-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): |
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* [mlabonne/OmniTruthyBeagle-7B-v0](https://huggingface.co/mlabonne/OmniTruthyBeagle-7B-v0) |
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* [mlabonne/NeuBeagle-7B](https://huggingface.co/mlabonne/NeuBeagle-7B) |
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* [mlabonne/NeuralOmniBeagle-7B](https://huggingface.co/mlabonne/NeuralOmniBeagle-7B) |
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## 🏆 Evaluation |
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The evaluation was performed using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval) on Nous suite. See the entire leaderboard [here](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard). |
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| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench | |
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|---|---:|---:|---:|---:|---:| |
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| [**Monarch-7B**](https://huggingface.co/mlabonne/Monarch-7B) [📄](https://gist.github.com/mlabonne/0b8d057c5ece41e0290580a108c7a093) | **62.68** | **45.48** | **77.07** | **78.04** | **50.14** | |
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| [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) [📄](https://gist.github.com/mlabonne/88b21dd9698ffed75d6163ebdc2f6cc8) | 52.42 | 42.75 | 72.99 | 52.99 | 40.94 | |
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| [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B) [📄](https://gist.github.com/mlabonne/14687f1eb3425b166db511f31f8e66f6) | 53.51 | 43.67 | 73.24 | 55.37 | 41.76 | |
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| [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B) [📄](https://gist.github.com/mlabonne/ad0c665bbe581c8420136c3b52b3c15c) | 60.25 | 46.06 | 76.77 | 70.32 | 47.86 | |
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| [eren23/dpo-binarized-NeuralTrix-7B](https://huggingface.co/eren23/dpo-binarized-NeuralTrix-7B) [📄](https://gist.github.com/CultriX-Github/dbdde67ead233df0c7c56f1b091f728c) | 62.5 | 44.57 | 76.34 | 79.81 | 49.27 | |
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| [CultriX/NeuralTrix-7B-dpo](https://huggingface.co/CultriX/NeuralTrix-7B-dpo) [📄](https://gist.github.com/CultriX-Github/df0502599867d4043b45d9dafb5976e8) | 62.5 | 44.61 | 76.33 | 79.8 | 49.24 | |
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## 🧩 Configuration |
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```yaml |
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models: |
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- model: mistralai/Mistral-7B-v0.1 |
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# no parameters necessary for base model |
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- model: mlabonne/OmniTruthyBeagle-7B-v0 |
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parameters: |
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density: 0.65 |
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weight: 0.36 |
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- model: mlabonne/NeuBeagle-7B |
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parameters: |
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density: 0.6 |
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weight: 0.34 |
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- model: mlabonne/NeuralOmniBeagle-7B |
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parameters: |
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density: 0.6 |
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weight: 0.3 |
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merge_method: dare_ties |
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base_model: mistralai/Mistral-7B-v0.1 |
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parameters: |
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int8_mask: true |
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dtype: bfloat16 |
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random_seed: 0 |
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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 = "mlabonne/Monarch-7B" |
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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/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__Monarch-7B) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |76.25| |
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|AI2 Reasoning Challenge (25-Shot)|73.04| |
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|HellaSwag (10-Shot) |89.03| |
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|MMLU (5-Shot) |64.41| |
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|TruthfulQA (0-shot) |77.35| |
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|Winogrande (5-shot) |84.61| |
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|GSM8k (5-shot) |69.07| |
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