--- license: apache-2.0 tags: - merge - mergekit - lazymergekit - udkai/Turdus - leveldevai/TurdusBeagle-7B - liminerity/Blur-7b-v1.21 base_model: - udkai/Turdus - leveldevai/TurdusBeagle-7B - liminerity/Blur-7b-v1.21 model-index: - name: BrurryDog-7b-v0.1 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: 72.53 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/BrurryDog-7b-v0.1 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: 88.37 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/BrurryDog-7b-v0.1 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: 64.74 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/BrurryDog-7b-v0.1 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: 70.05 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/BrurryDog-7b-v0.1 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: 82.87 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/BrurryDog-7b-v0.1 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: 66.87 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=222gate/BrurryDog-7b-v0.1 name: Open LLM Leaderboard --- # BrurryDog-7b-v0.1 BrurryDog-7b-v0.1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [udkai/Turdus](https://huggingface.co/udkai/Turdus) * [leveldevai/TurdusBeagle-7B](https://huggingface.co/leveldevai/TurdusBeagle-7B) * [liminerity/Blur-7b-v1.21](https://huggingface.co/liminerity/Blur-7b-v1.21) ## 🧩 Configuration ```yaml models: - model: udkai/Turdus parameters: density: [1, 0.7, 0.1] # density gradient weight: 1.0 - model: leveldevai/TurdusBeagle-7B parameters: density: 0.5 weight: [0, 0.3, 0.7, 1] # weight gradient - model: liminerity/Blur-7b-v1.21 parameters: density: 0.33 weight: - filter: mlp value: 0.5 - value: 0 merge_method: ties base_model: udkai/Turdus parameters: normalize: true int8_mask: true dtype: bfloat16 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "222gate/BrurryDog-7b-v0.1" 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_222gate__BrurryDog-7b-v0.1) | Metric |Value| |---------------------------------|----:| |Avg. |74.24| |AI2 Reasoning Challenge (25-Shot)|72.53| |HellaSwag (10-Shot) |88.37| |MMLU (5-Shot) |64.74| |TruthfulQA (0-shot) |70.05| |Winogrande (5-shot) |82.87| |GSM8k (5-shot) |66.87|