--- license: cc-by-nc-2.0 tags: - merge - mergekit - lazymergekit - SanjiWatsuki/Kunoichi-DPO-v2-7B - mlabonne/AlphaMonarch-7B base_model: - SanjiWatsuki/Kunoichi-DPO-v2-7B - mlabonne/AlphaMonarch-7B model-index: - name: kuno-dogwalker-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: 72.01 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-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: 88.17 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-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: 64.96 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-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: 71.39 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-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: 82.0 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-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: 71.11 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-7b name: Open LLM Leaderboard --- # kuno-dogwalker-7b # 🦮🦮🦮🥷 Decent metrics, but writing feels off compared to [kuno-royale-v2-7b](https://huggingface.co/core-3/kuno-royale-v2-7b). |Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K | |-------------------|---------|-----|-----------|------|------------|------------|-------| | eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO | 76.45 | 73.12 | 89.09 | 64.80 | 77.45 | 84.77 | 69.45 | | mlabonne/AlphaMonarch-7B | 75.99 | 73.04 | 89.18 | 64.40 | 77.91 | 84.69 | 66.72 | | **core-3/kuno-dogwalker-7b** | **74.94** | **72.01** | **88.17** | **64.96** | **71.39** | **82.00** | **71.11** | | core-3/kuno-royale-v2-7b | 74.80 | 72.01 | 88.15 | 65.07 | 71.10 | 82.24 | 70.20 | | core-3/kuno-royale-7B | 74.74 | 71.76 | 88.20 | 65.13 | 71.12 | 82.32 | 69.90 | | SanjiWatsuki/Kunoichi-DPO-v2-7B | 72.46 | 69.62 | 87.44 | 64.94 | 66.06 | 80.82 | 65.88 | | SanjiWatsuki/Kunoichi-7B | 72.13 | 68.69 | 87.10 | 64.90 | 64.04 | 81.06 | 67.02 | kuno-dogwalker-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-DPO-v2-7B) * [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B) ## 🧩 Configuration ```yaml slices: - sources: - model: SanjiWatsuki/Kunoichi-DPO-v2-7B layer_range: [0, 32] - model: mlabonne/AlphaMonarch-7B layer_range: [0, 32] merge_method: slerp base_model: SanjiWatsuki/Kunoichi-DPO-v2-7B parameters: t: - filter: self_attn value: [0, 0.5, 0.3, 0.7, 1] - filter: mlp value: [1, 0.5, 0.7, 0.3, 0] - value: 0.5 dtype: bfloat16 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "core-3/kuno-dogwalker-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"]) ```