--- license: cc-by-nc-4.0 tags: - dpo datasets: - yleo/emerton_dpo_pairs_judge base_model: mlabonne/Monarch-7B model-index: - name: EmertonMonarch-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: 72.7 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yleo/EmertonMonarch-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: 89.16 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yleo/EmertonMonarch-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: 64.05 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yleo/EmertonMonarch-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: 78.09 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yleo/EmertonMonarch-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: 85.16 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yleo/EmertonMonarch-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: 65.28 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yleo/EmertonMonarch-7B name: Open LLM Leaderboard --- --- # 🦜 EmertonMonarch-7B EmertonOmniBeagle-7B-dpo is a DPO fine-tune of [mlabonne/Monarch-7B](https://huggingface.co/mlabonne/OmniBeagle-7B) using the [yleo/emerton_dpo_pairs_judge](https://huggingface.co/datasets/yleo/emerton_dpo_pairs_judge) preference dataset created from [Intel/orca_dpo_pairs](https://huggingface.co/datasets/Intel/orca_dpo_pairs) by replacing gpt 3.5 answer by a gpt4 Turbo answer. Then, LLM-Blender is used to judge between GPT4 and GPT4 Turbo. ## 🔍 Applications This model uses a context window of 8k. It is compatible with different templates, like chatml and Llama's chat template. ## 🏆 Evaluation ### Open LLM Leaderboard To come... ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "yleo/EmertonMonarch-7B" messages = [{"role": "user", "content": "How to improve LLM fine-tuning?"}] 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_yleo__EmertonMonarch-7B) | Metric |Value| |---------------------------------|----:| |Avg. |75.74| |AI2 Reasoning Challenge (25-Shot)|72.70| |HellaSwag (10-Shot) |89.16| |MMLU (5-Shot) |64.05| |TruthfulQA (0-shot) |78.09| |Winogrande (5-shot) |85.16| |GSM8k (5-shot) |65.28|