--- license: cc-by-nc-4.0 tags: - merge - mergekit - lazymergekit base_model: - mlabonne/OmniTruthyBeagle-7B-v0 - mlabonne/NeuBeagle-7B - mlabonne/NeuralOmniBeagle-7B model-index: - name: Monarch-7B results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 73.04 name: normalized accuracy source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 89.03 name: normalized accuracy source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 64.41 name: accuracy source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 77.35 source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 84.61 name: accuracy source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 69.07 name: accuracy source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Monarch-7B name: Open LLM Leaderboard --- ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/zDCZ6uIu68k1JeCOa9bHl.jpeg) # Monarch-7B **Update 13/02/24: Monarch-7B is the best-performing model on the YALL leaderboard.** Monarch-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [mlabonne/OmniTruthyBeagle-7B-v0](https://huggingface.co./mlabonne/OmniTruthyBeagle-7B-v0) * [mlabonne/NeuBeagle-7B](https://huggingface.co./mlabonne/NeuBeagle-7B) * [mlabonne/NeuralOmniBeagle-7B](https://huggingface.co./mlabonne/NeuralOmniBeagle-7B) ## 🏆 Evaluation 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). | Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench | |---|---:|---:|---:|---:|---:| | [**Monarch-7B**](https://huggingface.co./mlabonne/Monarch-7B) [📄](https://gist.github.com/mlabonne/0b8d057c5ece41e0290580a108c7a093) | **62.68** | **45.48** | **77.07** | **78.04** | **50.14** | | [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 | | [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 | | [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 | | [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 | | [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 | ## 🧩 Configuration ```yaml models: - model: mistralai/Mistral-7B-v0.1 # no parameters necessary for base model - model: mlabonne/OmniTruthyBeagle-7B-v0 parameters: density: 0.65 weight: 0.36 - model: mlabonne/NeuBeagle-7B parameters: density: 0.6 weight: 0.34 - model: mlabonne/NeuralOmniBeagle-7B parameters: density: 0.6 weight: 0.3 merge_method: dare_ties base_model: mistralai/Mistral-7B-v0.1 parameters: int8_mask: true dtype: bfloat16 random_seed: 0 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "mlabonne/Monarch-7B" 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/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_mlabonne__Monarch-7B) | Metric |Value| |---------------------------------|----:| |Avg. |76.25| |AI2 Reasoning Challenge (25-Shot)|73.04| |HellaSwag (10-Shot) |89.03| |MMLU (5-Shot) |64.41| |TruthfulQA (0-shot) |77.35| |Winogrande (5-shot) |84.61| |GSM8k (5-shot) |69.07|